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Patent 2888116 Summary

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Claims and Abstract availability

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(12) Patent: (11) CA 2888116
(54) English Title: DYNAMIC SEARCH PARTITIONING
(54) French Title: PARTITIONNEMENT DE RECHERCHE DYNAMIQUE
Status: Granted
Bibliographic Data
(51) International Patent Classification (IPC):
  • G06F 12/02 (2006.01)
  • G06F 17/30 (2006.01)
  • H04L 12/927 (2013.01)
  • H04L 29/02 (2006.01)
(72) Inventors :
  • GOLDBERG, JONATHAN MICHAEL (United States of America)
  • HANDLER, JONATHAN BLAKE (United States of America)
  • MAKHANI, ASIF MANSOOR ALI (United States of America)
  • NWOKAH, EKECHI KARL EDOZLE (United States of America)
(73) Owners :
  • A9.COM, INC. (United States of America)
(71) Applicants :
  • A9.COM, INC. (United States of America)
(74) Agent: SMART & BIGGAR LP
(74) Associate agent:
(45) Issued: 2018-03-27
(86) PCT Filing Date: 2013-10-12
(87) Open to Public Inspection: 2014-04-17
Examination requested: 2015-04-10
Availability of licence: N/A
(25) Language of filing: English

Patent Cooperation Treaty (PCT): Yes
(86) PCT Filing Number: PCT/US2013/064731
(87) International Publication Number: WO2014/059394
(85) National Entry: 2015-04-10

(30) Application Priority Data:
Application No. Country/Territory Date
13/650,961 United States of America 2012-10-12
13/650,931 United States of America 2012-10-12

Abstracts

English Abstract


A dynamic search partitioning involves monitoring an amount of data being
stored or a rate at which
data is being manipulated on a first partition of each of two or more sets of
partitions provided by a
network service. Each set of partitions includes a plurality of partitions
included in a storage
allocation provided by the network service. If the amount or rate exceeds an
amount threshold or a
rate threshold, and if network traffic associated with the storage allocation
corresponds to a first type,
the size of the first partition is increased based on the network traffic
corresponding to the first type
and at least in part on the amount of data being stored or the rate at which
data is being manipulated.
The network traffic is directed to a cache provided by the network service
during the increase and to
the storage allocation when the increase is complete.


French Abstract

Selon l'invention, une entité utilisant un dispositif informatique peut transmettre des données consultables à un service de réseau pour être indexées et stockées. Les données peuvent inclure une pluralité de champs de données, chaque champ de données ayant une ou plusieurs valeurs associées. Le service de réseau peut analyser les champs de données et leurs valeurs associées respectivement pour déterminer des types de champs de données pour les champs de données et des options de recherche à activer pour les champs de données. Sur la base, au moins en partie, des types de champs de données et des options de recherche, le service de réseau peut générer une configuration/un schéma d'index de recherche. Sur la base, au moins en partie, de la configuration/du schéma d'index de recherche généré, le service de réseau peut générer un index de recherche pour les données. Dans certains modes de réalisation, le service de réseau peut également convertir les données en un format compatible avec l'index de recherche.

Claims

Note: Claims are shown in the official language in which they were submitted.


34
EMBODIMENTS IN WHICH AN EXCLUSIVE PROPERTY OR PRIVILEGE IS
CLAIMED ARE DEFINED AS FOLLOWS:
1. A computer-implemented method for dynamic search partitioning,
comprising:
monitoring at least one of an amount of data being stored or a rate at which
data is
being manipulated on a first partition of each of two or more sets of
partitions
provided by a network service, each set of partitions including a plurality of

partitions, the plurality of partitions being included in a storage allocation
provided
by the network service, each set of partitions associated with a different
account;
determining that the at least one of the amount or the rate exceeds a
specified amount
threshold or a specified rate threshold, respectively;
determining that network traffic associated with the storage allocation
corresponds to
a first type;
performing an increase to a size of the first partition, the increase being
based on the
network traffic corresponding to the first type and at least in part on the
amount of
data being stored or the rate at which data is being manipulated;
directing the network traffic to a cache provided by the network service
during the
increase; and
directing the network traffic to the storage allocation when the performing
the
increase is complete.
2. The computer-implemented method of claim I, further comprising:
monitoring a search index for the storage allocation;

35
detecting that a size of the search index exceeds a specified index size
threshold; and
updating the search index for the storage allocation to reflect the increase
with
respect to the storage allocation.
3. The computer-implemented method of claim 2, further comprising:
adding, in response to detecting that a size of the search index exceeds a
specified
index size threshold, at least a second partition to the set of partitions
when the size
of the first partition reaches a maximum partition size threshold.
4. A computer-implemented method comprising:
monitoring data usage on a storage allocation in a networked environment, the
storage allocation having a number of sets of partitions, each set of
partitions
associated with a different account and including at least two partitions;
determining whether the data usage on at least one partition of a set of
partitions
included in the storage allocation exceeds a specified threshold;
determining that network traffic associated with the storage allocation
corresponds to
a first type;
modifying a size of the at least one partition based on the network traffic
corresponding to the first type;
directing the network traffic away from a portion of the storage allocation
associated
with the modifying; and

36
directing the network traffic to the portion of the storage allocation
associated with
the modifying when the modifying is complete.
5. The computer-implemented method of claim 4, further comprising:
detecting that a size of a search index for the storage allocation exceeds a
specified
index size threshold; and
updating the search index for the storage allocation based on the modifying
the size
of the at least one partition.
6. The computer-implemented method of claim 5, wherein the updating the
search index
includes rebuilding the search index for the storage allocation to reflect the
modifying the
size of the at least one partition.
7. The computer-implemented method of any one of claims 4 ¨ 6, wherein the
data usage
includes at least one of an amount of data being stored on the storage
allocation or a rate at
which data is being manipulated on the storage allocation.
8. The computer-implemented method of claim 7, wherein the specified
threshold includes at
least one of a specified amount threshold or a specified rate threshold, and
wherein the data
usage exceeds the specified threshold when there is an occurrence of at least
one of the
amount of data being stored exceeds the specified amount threshold or the rate
at which
data is being manipulated exceeds the specified rate threshold.
9. The computer-implemented method of any one of claims 1 ¨ 8, wherein the
specified
threshold is calculated based at least in part on information about historical
data usage.

37
10. The computer-implemented method of any one of claims 4 ¨ 9, further
comprising:
determining that an amount of network traffic directed to the storage
allocation is
above a specified traffic threshold; and
modifying the storage allocation based on the amount of network traffic.
11. The computer-implemented method of any one of claims 4 ¨ 10, wherein
the network
traffic includes search query traffic for searching data stored on the storage
allocation.
12. The computer-implemented method of claim 10, wherein the modifying the
storage
allocation based on the amount of network traffic includes at least one of
modifying the
size of the at least one partition, modifying the number of partitions, or
replacing at least
one partition of the set of partitions with at least one partition having
different
specifications.
13. The computer-implemented method of claim 12, wherein the different
specifications
include at least one of a different CPU power, a different capacity of RAM, a
different
capacity of hard disk space, or a different capacity of bandwidth.
14. The computer-implemented method of any one of claims 4 ¨ 13, wherein
the modifying the
size of the at least one partition includes increasing the size of the at
least one partition if
the size of the at least one partition is below a maximum partition size
threshold.
15. The computer-implemented method of any one of claims 4 ¨ 13, wherein
the modifying the
size of the at least one partition includes decreasing the size of the at
least one partition,
and wherein the computer-implemented method further comprises decreasing the
number
of the partitions in the set of partitions when the number of the partitions
in the set of
partitions is greater than two partitions.

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16. The computer-implemented method of any one of claims 4 ¨ 15, further
comprising:
determining a CPU usage of the storage allocation, wherein the modifying the
size is
based on at least one of the data usage on the storage allocation or the
determined
CPU usage of the storage allocation.
17. The computer-implemented method of any one of claims 4 ¨ 16, further
comprising:
modifying a configuration of the storage allocation based on at least one of a

configuration associated with the data usage or a user-initiated input.
18. The computer-implemented method of any one of claims 4 ¨ 17, further
comprising:
determining when to perform the modifying of the size based on resources
available
to the storage allocation.
19. A system comprising:
a storage allocation having a number of sets of partitions, each set of
partitions
associated with a different account and including at least two partitions;
at least one processor; and
a memory device including instructions that, when executed by the at least one

processor, cause the system to:
monitor data usage on the storage allocation;
determine whether the data usage on at least one partition of a set of
partitions
included in the storage allocation exceeds a specified threshold;

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determine that network traffic associated with the storage allocation
corresponds to a first type;
modify a size of the at least one partition based on the network traffic
corresponding to the first type;
direct the network traffic away from a portion of the storage allocation
associated with the modifying; and
direct the network traffic to the portion of the storage allocation associated
with
the modifying when the modifying is complete.
20. The system of claim 19, further comprising:
at least one load balancer configured to facilitate in the network traffic
being directed
away from the portion of the storage allocation during the modifying the size
and in
the network traffic being directed to the portion of the storage allocation
when the
modifying the size is complete.
21. The system of claim 20, wherein the at least one load balancer is
configured to direct the
network traffic across the number of sets of partitions included in the
storage allocation.
22. The system of any one of claims 19 ¨ 21, further comprising:
at least one monitor module configured to facilitate in the monitoring the
data usage
on the storage allocation and in the determining whether the data usage on the
at least
one partition exceeds a specified threshold.

40
23. A non-transitory computer-readable storage medium including
instructions for identifying
elements, the instructions when executed by a processor of a computing system
causing the
computing system to:
monitor data usage on a storage allocation in a networked environment, the
storage
allocation having a number of sets of partitions, each set of partitions
associated with
a different account and including at least two partitions;
determine whether the data usage on at least one partition of a set of
partitions
included in the storage allocation exceeds a specified threshold;
determine that network traffic associated with the storage allocation
corresponds to a
first type;
modify a size of the at least one partition included in the storage allocation
based on
the network traffic corresponding to the first type;
direct the network traffic away from a portion of the storage allocation
associated
with the modifying; and
direct the network traffic to the portion of the storage allocation associated
with the
modifying when the modifying is complete.
24. The non-transitory computer-readable storage medium of claim 23,
wherein the
instructions cause the computing system to further detect that a size of a
search index for
the storage allocation exceeds a specified index size threshold and update the
search index
for the storage allocation based on the modifying the size of the at least one
partition.

41
25. The
non-transitory computer-readable storage medium of claim 24, wherein the
updating
the search index includes rebuilding the search index for the storage
allocation to reflect
the modifying the size of the at least one partition.

Description

Note: Descriptions are shown in the official language in which they were submitted.


DYNAMIC SEARCH PARTITIONING
BACKGROUND
[0001] Computing devices are often used to communicate over a network such
as the
Internet. Network based services offered by a service provider are becoming
more commonplace.
Computing devices are frequently used to connect to a network based service,
which can provide
services such as storing searchable data to be used/retrieved by the computing
devices or
providing additional processing power to the computing devices. With respect
to the network
based storage of searchable data, users of computing devices typically need to
choose a
configuration and/or format for their data, so that their data can be indexed
and stored by the
network based service. Conventional approaches typically require users to
determine an
appropriate configuration for their data. Conventional approaches can also
demand a format to
which the user's data must comply, thereby requiring the users to convert
their data to the format.
This can be inconvenient, cumbersome, or difficult to users who want to use
the network based
service for storage and search, thereby reducing the overall user experience.
SUMMARY
[0001a] In one embodiment, there is provided a computer-implemented method
for dynamic
search partitioning. The method involves monitoring at least one of an amount
of data being
stored or a rate at which data is being manipulated on a first partition of
each of two or more sets
of partitions provided by a network service. Each set of partitions includes a
plurality of
partitions. The plurality of partitions are included in a storage allocation
provided by the network
service. Each set of partitions is associated with a different account. The
method further involves
determining that the at least one of the amount or the rate exceeds a
specified amount threshold
or a specified rate threshold, respectively; determining that network traffic
associated with the
storage allocation corresponds to a first type; and performing an increase to
a size of the first
partition. The increase is on the network traffic corresponding to the first
type and at least in part
on the amount of data being stored or the rate at which data is being
manipulated. The method
further involves directing the network traffic to a cache provided by the
network service during
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the increase, and directing the network traffic to the storage allocation when
the performing the
increase is complete.
[0001b] In another embodiment, there is provided a computer-implemented
method. The
computer-implemented method involves monitoring data usage on a storage
allocation in a
networked environment. The storage allocation has a number of sets of
partitions, and each set of
partitions is associated with a different account and includes at least two
partitions. The
computer-implemented method further involves determining whether the data
usage on at least
one partition of a set of partitions included in the storage allocation
exceeds a specified
threshold, and determining that network traffic associated with the storage
allocation corresponds
to a first type. The computer-implemented method further involves modifying a
size of the at
least one partition based on the network traffic corresponding to the first
type, directing the
network traffic away from a portion of the storage allocation associated with
the modifying, and
directing the network traffic to the portion of the storage allocation
associated with the
modifying when the modifying is complete.
[0001c] In another embodiment, there is provided a system. The system
includes a storage
allocation having a number of sets of partitions. Each set of partitions is
associated with a
different account and includes at least two partitions. The system further
includes at least one
processor, and a memory device including instructions that, when executed by
the at least one
processor, cause the system to monitor data usage on the storage allocation,
and determine
whether the data usage on at least one partition of a set of partitions
included in the storage
allocation exceeds a specified threshold. The instructions further cause the
system to: determine
that network traffic associated with the storage allocation corresponds to a
first type; modify a
size of the at least one partition based on the network traffic corresponding
to the first type;
direct the network traffic away from a portion of the storage allocation
associated with the
modifying; and direct the network traffic to the portion of the storage
allocation associated with
the modifying when the modifying is complete.
[0001d] In another embodiment, there is provided a non-transitory computer-
readable storage
medium including instructions for identifying elements. The instructions, when
executed by a
processor of a computing system, cause the computer system to monitor data
usage on a storage

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allocation in a networked environment. The storage allocation has a number of
sets of partitions.
Each set of partitions is associated with a different account and includes at
least two partitions.
The instructions further cause the computer system to: determine whether the
data usage on at
least one partition of a set of partitions included in the storage allocation
exceeds a specified
threshold; determine that network traffic associated with the storage
allocation corresponds to a
first type; modify a size of the at least one partition included in the
storage allocation based on
the network traffic corresponding to the first type; direct the network
traffic away from a portion
of the storage allocation associated with the modifying; and direct the
network traffic to the
portion of the storage allocation associated with the modifying when the
modifying is complete.
BRIEF DESCRIPTION OF THE DRAWINGS
[0002] Various embodiments in accordance with the present disclosure will
be described
with reference to the drawings, in which:
[0003] FIG. 1 illustrates an example environment in which aspects of the
various
embodiments can be utilized;
[0004] FIG. 2 illustrates an example system embodiment for index
configuration for
searchable data in a networked environment;
[0005] FIG. 3 illustrates an example web browsing environment in which
index
configuration for searchable data in a networked environment can be utilized;
[0006] FIG. 4 illustrates an example search index that can be generated in
accordance with
the various embodiments;
[0007] FIG. 5 illustrates an example method embodiment for index
configuration for
searchable data in a networked environment;

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100081 FIG. 6 illustrates an example device that can be used to implement
aspects of
the various embodiments;
[0009] FIG. 7 illustrates example components of a client device such as that
illustrated in FIG. 6; and
[0010] FIG. 8 illustrates an environment in which various embodiments can be
implemented.
DETAILED DESCRIPTION
[0011] Systems and methods to generate an index configuration that can be used
to
generate a search index for data received over at least one network are
described. At
least some embodiments enable a computing device to upload data over a network
(e.g.,
the Internet) onto a storage allocation provided by a network service (i.e.,
network
service provider). The network service can analyze the uploaded data to
determine a
type of data field (i.e., data field type) for each data field in the
plurality of data fields.
The network service can analyze the uploaded data to determine whether or not
to
enable one or more search options for each data field in the plurality of data
fields
included in the uploaded data.
[0012] At least some embodiments enable a computing device to upload data over
a
network (e.g., the Internet) onto a storage allocation provided by a network
service (i.e.,
network service provider, network based service, etc.). One or more
users/entities (e.g.,
using one or more computing devices) can search for the uploaded data over the

network utilizing a search index, which can be provided by the network
service.
[0013] In some embodiments, the uploaded data can include a plurality of data
fields.
The network service can analyze the uploaded data to determine a type of data
field
(i.e., data field type) for each data field in the plurality of data fields.
For example, each
data field can be of a type including an integer type, a text type, or a
literal type.
[0014] Moreover, the network service can analyze the uploaded data to
determine
whether or not to enable one or more search options for each data field in the
plurality
of data fields included in the uploaded data. For example, the network service
can
determine, for each respective data field, whether or not to enable an option
that would
include the respective data field in a search index to be generated. The
network service

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can also determine, for each respective data field, whether to enable an
option that
would calculate a facet count for the respective data field. Further, the
network service
can determine, for each respective data field, whether to enable an option
that would
return/provide the value associated with the respective data field in response
to a search
query.
100151 In some embodiments, the network service can generate an index
configuration (i.e., search index configuration, schema, index settings, etc.)
for the data
based at least in part on the determined data field type(s) and the search
option(s) to be
enabled. The network service can generate a search index for the data based at
least in
part on the index configuration.
[0016] Various other functions and advantages are described and suggested
below as
may be provided in accordance with the various embodiments.
[0017] FIG. 1 illustrates an example environment 100 in which aspects of the
various
embodiments can be utilized. The example environment 100 can comprise at least
one
computing device 102, a network 104 (e.g., Internet, intranet, local network,
local area
network, etc.), and a network service 106 (i.e., network service provider,
network based
service, etc.). The at least one computing device 102 can be communicatively
connected to the network service 106 over the network 104. In some
embodiments, the
computing device 102 can communicate the network service 106 without a network
104
such as the Internet. As shown in FIG. 1, there can also be a user 108 of the
at least one
computing device 102 or other entity (e.g., individual, company, organization,
group,
etc.) 108. The user or entity 108 can communicate data 110 from the at least
one
computing device 102 over the network 104 to the network service 106 (and vice
versa).
[0018] In some embodiments, the network service 106 can comprise of and/or
utilize
one or more hosts or servers connected to the network 104. For example, the
network
service 106 can rent storage space to customers, such as the user of the
device 102 or
another entity(ies) (e.g., company, organization, group, individual, etc.)
108.
Accordingly, the user/entity 108 of the computing device 102 can store data
from the
device 102 onto the network service 106 using the network 104. In other words,
the
user/entity 108 and/or device 102 can utilize network based computing storage
via the
network service 106.

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100191 In one example, the computing device 102 can transmit data 110 over the

network 104 to be stored on the network service 106, as shown in FIG. 1. The
data 110
can be any data utilized in network based computing, such as for search,
database
storage, running an application, running a virtual machine, running an
operating system,
etc. The computing device 102 can transmit the data 110 to be stored on a
storage
allocation provided by the service 106. For example, the user/entity 108 can
purchase
or rent storage space on the service 106 and the storage allocation can be
allocated and
assigned to the user/entity 108. In some embodiments, the user/entity 108 can
have a
particular account and/or storage allocation on the service 106; the storage
space (e.g.,
storage allocation) allocated and assigned to the entity 108 can be associated
with the
account for the entity 108.
[0020] The entity 108 may also want the network service 106 to provide a
search
index for the data 110. Conventional approaches typically require the entity
108 to first
provide a configuration (i.e., index configuration, schema, index setting,
etc.) for the
data 110 to be indexed, or conventional approaches can require a
configuration/format
(e.g., Search Data Format (SDF)) that the entity's data 110 must comply with,
thus
demanding the entity 110 to convert its data 110 to the required
configuration.
However, this can be inconvenient, cumbersome, or difficult to the entity 108.
[0021] In some embodiments, the entity 108 can transmit the data 110 to the
network
service 106, and the network service 106 can automatically (i.e., without an
instruction
or a request from the entity 108) analyze the data 110 and generate an index
configuration (e.g., search index configuration, search index schema, etc.)
for the data
110. For example, in some embodiments, the network service 106 can analyze the
data
110 by determining a type of data field 112 for one or more data fields
included in the
data 110 and determining a search option 114 to be enabled for one or more
data fields
included in the data 110.
[0022] With regard to determining the type of data field 112, there can be a
plurality
of data field types that the data 110 (e.g., document, file, etc.) can be
associated with,
such as an integer type of data field, a literal type of data field, or a text
type of data
field, and so forth. In some embodiments, the data 110 can include a plurality
of data
fields, each data field including a value (e.g., data field "name" can have a
value of
"ABCD-Brand Shirt"; data field "Price" can have a value of "$20'; etc.). The
network

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service 106 can analyze the plurality of data fields included in the data 110
to determine
a data field type for each data field in the plurality.
[0023] For example, for each data field, the network service 106 can determine

whether the value of each respective data field comprises an amount of
integers above a
specified integer amount threshold (c.g., value of data ficld "Price" is all
integers); if so,
then that respective data field can be determined to be of an integer data
field type. The
network service 106 can also determine whether a data field is of a literal
data field type
by, for example, determining at least one of a value associated with the data
field having
an amount of alphabetic characters above a specified lower literal amount
threshold but
below a specified upper literal amount threshold, a number of distinct values
associated
with the data field being below a specified literal distinct amount threshold,
a
percentage of distinct values being below a specified literal distinct
percentage
threshold, or a length of values being below a specified literal length
threshold. In some
embodiments, the network service 106 can, for example, consider the length of
a data
field value and the frequency and/or percentage of distinct values in the data
field value
to identify the data field as being of a text type; if there are many distinct
values in a
data field value and the data field value is very long (e.g., has a number of
alphanumeric
characters above a threshold), then the data field is likely of a text type.
In some
embodiments, if a data field is not of an integer type or a literal type, then
the data field
can be of a text type.
[0024] Regarding determining the search option 114, the network service 106
can
determine one or more search options 114 to be enabled for (the data fields
of) the data
110. For example, having determined a data field type for a data field
included in the
data 110, the network service 106 can determine whether or not to enable an
option to
include the data field in the search index to be generated, whether or not to
enable an
option to calculate a facet count for the data field, and/or whether or not to
enable an
option to return/provide a search value for the data type.
[0025] For example, if the data field type for a data field is determined to
be a text
(e.g., the data field is a "Product Description" and the value is a long
paragraph), then
the network service 106 can choose the option not to include the data field
(and value)
in the search index. In another example, for data field with an integer data
field type
(e.g., data field being "Production Year" and the value is a year), the
network service
106 can choose to enable the option to include the data field in the search
index to be

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generated, and the service 106 can enable the option to calculate a facet
count for the
data field. A facet count can be a count of how many search results fall into
a certain
category for a data field. For example, if the data field is "Production
Year," the
network service 106 can determine that it makes sense to provide a facet
count, which
indicates how many search results are associated with a certain category;
e.g., "1984
(23), 2002 (12), 2010 (18)" shows an example of facet counts in which 23
search results
are associated with "1984" with respect to the "Production Year" data field,
12 search
results are associated with "2002," and 18 search results are associated with
"2010."
[0026] In some embodiments, the network service 106 can also decide to enable
the
return of the value for a data field. For example, not all searchable data
fields (and
values) need to be returned (e.g., retrieved and presented) in response to a
search
request. The network service 106 can decide whether or not to return the value
for a
data field.
[0027] Turning now to the generating of a configuration for the data 110, the
network
service can automatically (i.e., without an instruction from the entity 108)
generate a
configuration (e.g., search index configuration, schema, etc.) for the data
110. In some
embodiments, the configuration can, at least in part, help determine how to
index the
data 110; the index configuration can, at least in part, govern how the data
110 will be
indexed. The configuration or schema can specify a data field type for each
data field
included in the data 110, indicate whether each data field is searchable,
indicate whether
each data field is rankable (e.g., sortable), and other similar information
useful for
building the index. Subsequent to generating the configuration for the data
110 to be
indexed, the network service 106 can generate a search index for the data 110
based in
at least part on the generated configuration.
[0028] FIG. 2 illustrates an example web browsing environment 200 in which
index
configuration for searchable data in a networked environment can be utilized.
The
example web browsing environment 200 can comprise an example web page 202
being
rendered by an application, such as a web browser. In this example, the web
page 202
can be provided by a network service that is associated with the domain,
ABCD.com.
[0029] A user/entity (e.g., customer of the network service) can be a retailer
and can
upload data that is related to selling shirts, for example. The data can be
indexed and
stored by the network service and made searchable to others such as potential
customers

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of the user/entity. The network service can analyze the data to determine a
type of data
field (i.e., data field type) for each of the data fields included in the
data. For example,
the data related to the selling of shirts can include data fields such as
"Color" 206,
"Size" 208, "Price" 210, "Description," and other fields. The network service
can
analyze the value for each data field to determine a type for each respective
data field.
The network service can also determine one or more options (e.g., search
options) to
enable for each data field. The network service can subsequently generate a
configuration/schema for the data to be indexed. Then the network service can
generate
an index for the data based on the configuration/schema.
[0030] For example, the network service can identify the data field "Color"
and
determine that its value (e.g., "Red," "Blue," "White," "Green," etc.) is
alphabetic/literal
and may identity the type of the "Color" data field to be a literal type. (In
this example,
the data associated with the "Color" data field and the values (e.g., "Red,"
"Blue,"
"White," "Green," etc.) can be uploaded by the entity.) In another example,
the network
service can identify a "Size" data field in at least a portion of the uploaded
data and
determine that the values contained in the "Size" data field are numeric
values. In this
instance, the network service may determine that the "Size" data field is an
integer type.
In a further example, the network service can identify the values for the
"Description"
data fields in at least a portion of the uploaded data and may determine that
the values
include both numbers and alphabetic characters, and/or that the values are
lengthy in
terms of the number of characters, and/or that the values have distinct
terms/phrases/symbols. In this instance, the network service may determine
that the
"Description" data field is a text type.
[0031] Regarding the search options, the network service can determine, for
each of
the data fields, whether to not to enable the option to include a respective
data field in
the search index to be generated. For example, in some embodiments, the
"Description"
data fields (and corresponding values) can be omitted from the search index.
If so, then
when a query is run with respect the search index, the query will not search
the
"Description" data field. However, some embodiments can and do include the
"Description" data fields and values in the search index.
[0032] Moreover, the network service can determine whether or not to enable
the
option to calculate a facet count for each data field. As mentioned above, a
facet count
represents how many of the results matching a search query have a particular
value (or

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range of values) for a particular data field. For example, as shown in FIG. 2,
the
"Color" data field with a value of "Red" has a facet count of 23 (i.e., 23
search results
for a "Red" shirt), whereas the "Blue" value of the "Color" data field has a
facet count
of 28 (i.e., 28 search results for a "Blue" shirt), and so forth. In some
embodiments, the
values can overlap (i.e., do not have to be an exact match). For example, a
shirt with
blue and red stripes can be associated with both the "Blue" and "Red" values,
and/or
with other values. In some embodiments, the network service can determine that
facet
counts should be calculated for some of the data fields, but not necessarily
all of the data
fields. For example, the network service can determine that there should be
facet counts
for "Color," "Size," and "Price," but not for "Description."
[0033] Furthermore, the network service can determine whether or not to enable
a
return of the value for a data field. For example, there can be a data field
"Internal
Product Identification Number" included in the data, the value of the data
field being a
product identification number internal to the entity and not intended to be
shown to a
customer of the entity; as such, the network service can determine not to
enable a return
of the value for such a data field.
[0034] It is contemplated that there can be additional options as well as data
related to
other items that a person having ordinary skill in the art would recognize.
For example,
the network service can determine whether or not to enable an option to make a
data
field rankable (e.g., sortable). With reference to FIG. 2, in some
embodiments, the
"Price" data field can be ranked/sorted by its values (e.g., from lowest price
to highest
price, from highest price to lowest price, etc.), the "Color" data field can
be sorted
alphabetically (not illustrated in FIG. 2), and so forth. In another example
(not
illustrated), there can be data related to media files, such as music, videos,
books,
photographs, etc. Example data fields for the media files can include, but are
not
limited to, "Title," "Artist/Author," "Year Created," "Price," "Rating," etc.
[0035] Having determined the types of the data fields included in the data and
the one
or more search options for the data fields included in the data, the network
service can
generate a configuration (i.e., search index configuration, schema, etc.) for
the data, the
generating of the configuration being based at least in part on the determined
data field
types and search options.

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100361 Subsequent to generating the configuration, the network service can
generate a
search index for the data based at least in part on the generated
configuration.
Accordingly, the data provided by the entity can be stored with the network
service and
the search index for the data generated by the network service.
[0037] FIG. 3 illustrates an example system embodiment 300 for index
configuration
for searchable data in a networked environment. The example system embodiment
300
can comprise a system controller 302, at least one communication transceiver
304, a
data field type analyzer 306, a search option analyzer 308, an index
configuration
generator 310, an index generator 312, and at least one storage allocation
314.
[0038] The system controller 302 can facilitate the system to perform various
operations for index configuration for searchable data in a networked
environment. The
system controller 302 can communicate with the at least one communications
transceiver 304 to facilitate data transmission to and/or data receipt from
one or more
sources external to the system 300 as well as to facilitate data communication
among
the system.
[0039] Data received (e.g., from an entity) by the system 300 via the
communications
transceiver 304 can be analyzed by the data field type analyzer 306 to
determine a type
associated with each of the data fields included in the data. The data can
also be
analyzed by the search option analyzer 308 to determine whether or not to
enable one or
more search options with respect to each of the data fields included in the
data. Based
at least in part on the determined data field types and the one or more
determined search
options, the index configuration generator 310 can generate a search index
configuration/schema. Then based at least in part on the generated search
index
configuration/schema, the index generator 312 can generate a search index for
the data.
The data and the search index generated for the data can be stored on one or
more
storage allocations 314.
[0040] It is contemplated that the various components and/or portions of the
example
system 300 can be implemented as hardware, software, or a combination of both.
For
example, the various parts of the system 300 can be implemented via a circuit,
a
processor, an application, a portion of programming code, an algorithm, or any

combination thereof, etc. It is also contemplated FIG. 3 is an example and
meant to be
used for illustrative purposes only. For example, the various components do
not have to

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be configured according to FIG. 3. In some embodiments, the various components
do
not have to be tightly coupled to one another and can instead be spread across
a more
distributed system. For example, a component such as the index generator can
reside on
a separate/different network and/or system, but still retain a communicative
connection(s) to the other components.
100411 FIG. 4 illustrates an example search index 400 that can be generated in

accordance with the various embodiments of the present disclosure. With
reference to
FIG. 4, there can be a root node 402 in the search index. In the example of
FIG. 4, data
can be uploaded by an entity such as a T-Shirt retailer. The data can
correspond to
information about the T-Shirts (root node 402) that the entity has made
available for
sale. There can be parent nodes (e.g., 404, 406, 408) that represent data
fields for the
data relating to the T-Shirts. For example, the T-Shirts can have a Color data
field 404,
a Size data field 406, and a Price data field 408.
[0042] Continuing with the example of FIG. 4, the data fields can have child
nodes
(e.g., 410, 412, 414, 416, 418) that represent values within each respective
data field.
For example, there can be at least two Colors (Red 410 and Blue 412), one Size

(Medium 414), and two Price ranges (<$10 416 and $10-$20 418). There can also
be a
set of search results/items (e.g., T-Shirts 420, 422, 424, 426,428, 430) that
can
correspond to one or more of the data fields and values.
[0043] In this example, all three data fields (Color 404, Size 406, and Price
408) are
to be included in the search index, can have facet counts, and can
provide/return values
in response to relevant search queries. For example, as shown in FIG. 4,
Color:Red 410
can have a facet count of three and Color:Blue 412 can have a facet count of
two.
Size:Medium 414 can have a facet count of two. Price:<$10 416 can have a facet
count
of one and Price:$10-$20 418 can have a facet count of two. Moreover, a search
query
of Color:Red 410, for example, will return T-Shirts 422, 424, and 428;
searching for
Red 410 and Blue 412, for example, will return T-Shirt 422; and so forth.
Although the
example search index 400 is shown as a being a tree structure, it is
contemplated that the
search index can be generated in many other ways and/or with other structures.
[0044] FIG. 5 illustrates an example method embodiment 500 for index
configuration
for searchable data in a networked environment. Again, it should be understood
that
there can be additional, fewer, or alternative steps performed in similar or
alternative

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orders, or in parallel, within the scope of the various embodiments unless
otherwise
stated. At step 502, the example method embodiment 500 can receive data to be
indexed. For example, the method 500 can receive data, uploaded by an entity,
to be
indexed and the data can include a plurality of data fields (or at least one
data field). In
some embodiments, the example method can also determine a name for a data
field
associated with the data. At step 504, the example method 500 can determine a
type of
a data field associated with the data. For example, the method can determine a
field
type, of a plurality of field types, associated with each data field in the
plurality of data
fields. The plurality of field types can include (but is not limited to) at
least one of an
integer type, a literal type, or a text type. The type of the data field call
be determined
from a plurality of types of data fields. In some embodiments, the plurality
of data
fields and their types and/or names can be identified based on tags, signals,
or other
indications. The method 500 can determine one or more search options to be
enabled
with respect to the data field associated with the data, at step 506. For
example, the one
or more search options can include at least one of an option to include a
respective data
field in a search index to be generated, an option to calculate a facet count
for the
respective data field, or an option to provide one or more values associated
with the
respective data field. Step 508 can include generating an index configuration
for the
data based at least in part on the type of the data field and the one or more
search
options. Then at step 510, the method 500 can generate a search index for the
data
based at least in part on the index configuration for the data. In some
embodiments, the
search index can be generated based on whether the data is structured data,
free text
data, or a combination of both. In some embodiments, the example method can
also
provide at least one of the data, the index configuration, or the index to be
searchable by
one or more search queries.
[0045] There can be various other information included in index
configurations. For
example, a configuration can hold information regarding whether a data field
is
facetable or not (i.e., whether or not a facet count should be calculated for
the data
field), whether a data field is rankable or not (i.e., whether or not the
values of search
results having the data field should be sorted), etc.
[0046] In some embodiments, the network service can convert data
received/uploaded
in a first format to a second format, the second format being compatible with
the search
index and can store the data converted to the second format on one or more
storage

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allocations. For example, the network service can receive data from the
entity, the data
capable of having any one or more of several various formats, such as .PDF,
.DOC,
.DOCX, .CSV, .JSON, .XML, etc. The network service can automatically convert
the
data into a format compatible with (e.g., recognizable by, workable with,
etc.) the
network service, such as the Search Data Format (SDF).
100471 In some embodiments, the network service can covert the data based on
comparing the first format with the second format and modifying at least one
data field
associated with the first format to correspond to at least one data field
associated with
the second format. For example, the network service can compare a format(s) of
the
data received from the entity and modify/update the format such that it is
compatible
with the network service. This can include identifying whether one or more
data fields
in the format should be added, removed, or changed.
[0048] In some embodiments, the network service can determine a type of a data
field
to be the integer type based on determining that a value associated with the
data field
has an amount of integer characters above a specified integer amount
threshold. Also,
the network service can determine a type of a data field to be the literal
type
determining at least one of a value associated with the data field having an
amount of
alphabetic characters above a specified lower literal amount threshold but
below a
specified literal amount threshold, a number of distinct values associated
with the data
field being below a specified literal distinct amount threshold, a percentage
of distinct
values being below a specified literal distinct percentage threshold, or a
length of values
being below a specified literal length threshold. Further, the network service
can
determine a type of a data field to be the text type based on determining that
a value
associated with the data field has at least one of an amount of integer and
alphabetic
characters above a specified text amount threshold, a number of distinct
characters
above a specified text distinct amount threshold, a percentage of distinct
characters
above a specified text distinct percentage threshold, or a length of
characters above a
specified text length threshold.
[0049] In some embodiments, the network service can decide to enable the
option to
include a data field in a search index to be generated, the decision being
based at least in
part on receiving a signal included in the data field indicating that the data
field is to be
included in the search index. The network service can also decide to enable
the option
to calculate a facet count for a data field, the decision being based at least
in part on

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determining that a quantity for at least one value associated with the data
field is above
a specified facet count lower threshold and below a specified facet count
upper
threshold. The network service can further decide to enable the option to
provide a
value associated with a data field in response to a relevant search query, the
decision
being based at least in part on receiving a signal included in the data field
indicating that
the value associated with the data field is to be provided.
[0050] In some embodiments, one or more search queries (e.g., terms in the
search
query) can be utilized by the network service. For example, the network
service can
infer from the search queries that a searcher is faeeting on a particular data
field. As a
result, the network service can determine that the data field should be of a
literal type,
for example.
[0051] In some embodiments, when a searcher inputs query terms and requests a
search, one or more search results can be presented in a particular rank
expression (e.g.,
order of results), such as by relevance. The present disclosure can allow for
creations
more complicated rank expressions that take into account other factors such as
query
independent factors (e.g., there can be a popularity data field included
within the data,
etc.). The present disclosure can also allow for analysis to propose rank
expressions
that can be used, by looking at the data and determining that a data field is
meaningful
in terms of popularity. For example, there can be a text body data field type
and its
length (e.g., or the inverse of its length) can be taken into account and can
provide
useful information for rank expressions.
[0052] In some embodiments, data field types can also include a geolocation
type, a
time type, a date type, or a floating point number type.
[0053] Various embodiments consistent with the present disclosure can also
utilize
sample data. For example, the user/entity can first provide sample data to the
network
service. The network service can analyze the sample data to determine types of
data
fields and search options. Based on the data field types and search options
for the
sample data, the network service can generate an index configuration, and
subsequently
generate a search index based on the generated index configuration.
[0054] FIG. 6 illustrates an example electronic user device 600 that can be
used in
accordance with various embodiments. Although a portable computing device
(e.g., an
electronic book reader or tablet computer) is shown, it should be understood
that any

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electronic device capable of receiving, determining, and/or processing input
can be used
in accordance with various embodiments discussed herein, where the devices can

include, for example, desktop computers, notebook computers, personal data
assistants,
smart phones, video gaming consoles, television set top boxes, and portable
media
players. In some embodiments, a computing device 600 can be an analog device,
such
as a device that can perform signal processing using operational amplifiers.
In this
example, the computing device 600 has a display screen 602 on the front side,
which
under normal operation will display information to a user facing the display
screen (e.g.,
on the same side of the computing device as the display screen). The computing
device
in this example includes at least one camera 604 or other imaging element for
capturing
still or video image information over at least a field of view of the at least
one camera.
In some embodiments, the computing device might only contain one imaging
element,
and in other embodiments the computing device might contain several imaging
elements. Each image capture element may be, for example, a camera, a charge-
coupled device (CCD), a motion detection sensor, or an infrared sensor, among
many
other possibilities. If there are multiple image capture elements on the
computing
device, the image capture elements may be of different types. In some
embodiments, at
least one imaging element can include at least one wide-angle optical element,
such as a
fish eye lens, that enables the camera to capture images over a wide range of
angles,
such as 180 degrees or more. Further, each image capture element can comprise
a
digital still camera, configured to capture subsequent frames in rapid
succession, or a
video camera able to capture streaming video.
10055] The example computing device 600 also includes at least one microphone
606
or other audio capture device capable of capturing audio data, such as words
or
commands spoken by a user of the device. In this example, a microphone 606 is
placed
on the same side of the device as the display screen 602, such that the
microphone will
typically be better able to capture words spoken by a user of the device. In
at least some
embodiments, a microphone can be a directional microphone that captures sound
information from substantially directly in front of the microphone, and picks
up only a
limited amount of sound from other directions. It should be understood that a
microphone might be located on any appropriate surface of any region, face, or
edge of
the device in different embodiments, and that multiple microphones can be used
for
audio recording and filtering purposes, etc.

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100561 The example computing device 600 also includes at least one orientation

sensor 608, such as a position and/or movement-determining element. Such a
sensor
can include, for example, an accelerometer or gyroscope operable to detect an
orientation and/or change in orientation of the computing device, as well as
small
movements of the device. An orientation sensor also can include an electronic
or digital
compass, which can indicate a direction (e.g., north or south) in which the
device is
determined to be pointing (e.g., with respect to a primary axis or other such
aspect). An
orientation sensor also can include or comprise a global positioning system
(GPS) or
similar positioning element operable to determine relative coordinates for a
position of
the computing device, as well as information about relatively large movements
of the
device. Various embodiments can include one or more such elements in any
appropriate
combination. As should be understood, the algorithms or mechanisms used for
determining relative position, orientation, and/or movement can depend at
least in part
upon the selection of elements available to the device.
[0057] FIG. 7 illustrates a logical arrangement of a set of general components
of an
example computing device 700 such as the device 600 described with respect to
FIG. 6.
In this example, the device includes a processor 702 for executing
instructions that can
be stored in a memory device or element 704. As would be apparent to one of
ordinary
skill in the art, the device can include many types of memory, data storage,
or non-
transitory computer-readable storage media, such as a first data storage for
program
instructions for execution by the processor 702, a separate storage for images
or data, a
removable memory for sharing information with other devices, etc. The device
typically will include some type of display element 706, such as a touch
screen or liquid
crystal display (LCD), although devices such as portable media players might
convey
information via other means, such as through audio speakers. As discussed, the
device
in many embodiments will include at least one image capture element 708 such
as a
camera or infrared sensor that is able to image projected images or other
objects in the
vicinity of the device. Methods for capturing images or video using a camera
element
with a computing device are well known in the art and will not be discussed
herein in
detail. It should be understood that image capture can be performed using a
single
image, multiple images, periodic imaging, continuous image capturing, image
streaming, etc. Further, a device can include the ability to start and/or stop
image
capture, such as when receiving a command from a user, application, or other
device.

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The example device similarly includes at least one audio capture component
712, such
as a mono or stereo microphone or microphone array, operable to capture audio
information from at least one primary direction. A microphone can be a uni-or
omni-
directional microphone as known for such devices.
[0058] In some embodiments, the computing device 700 of FIG. 7 can include one
or
more communication elements (not shown), such as a Wi-Fi, Bluetooth, RF,
wired, or
wireless communication system. The device in many embodiments can communicate
with a network, such as the Internet, and may be able to communicate with
other such
devices. In some embodiments the device can include at least one additional
input
device able to receive conventional input from a user. This conventional input
can
include, for example, a push button, touch pad, touch screen, wheel, joystick,
keyboard,
mouse, keypad, or any other such device or element whereby a user can input a
command to the device. In some embodiments, however, such a device might not
include any buttons at all, and might be controlled only through a combination
of visual
and audio commands, such that a user can control the device without having to
be in
contact with the device.
[0059] The device 700 also can include at least one orientation or motion
sensor 710.
As discussed, such a sensor can include an accelerometer or gyroscope operable
to
detect an orientation and/or change in orientation, or an electronic or
digital compass,
which can indicate a direction in which the device is determined to be facing.
The
mechanism(s) also (or alternatively) can include or comprise a global
positioning
system (GPS) or similar positioning element operable to determine relative
coordinates
for a position of the computing device, as well as information about
relatively large
movements of the device. The device can include other elements as well, such
as may
enable location determinations through triangulation or another such approach.
These
mechanisms can communicate with the processor 702, whereby the device can
perform
any of a number of actions described or suggested herein.
[0060] As an example, a computing device such as that described with respect
to FIG.
6 can capture and/or track various information for a user over time. This
information
can include any appropriate information, such as location, actions (e.g.,
sending a
message or creating a document), user behavior (e.g., how often a user
performs a task,
the amount of time a user spends on a task, the ways in which a user navigates
through
an interface, etc.), user preferences (e.g., how a user likes to receive
information), open

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applications, submitted requests, received calls, and the like. As discussed
above, the
information can be stored in such a way that the information is linked or
otherwise
associated whereby a user can access the information using any appropriate
dimension
or group of dimensions.
[0061] As discussed, different approaches can be implemented in various
environments in accordance with the described embodiments. For example, FIG. 8

illustrates an example of an environment 800 for implementing aspects in
accordance
with various embodiments. As will be appreciated, although a Web-based
environment
is used for purposes of explanation, different environments may be used, as
appropriate,
to implement various embodiments. The system includes an electronic client
device
802, which can include any appropriate device operable to send and receive
requests,
messages or information over an appropriate network 804 and convey information
back
to a user of the device. Examples of such client devices include personal
computers,
cell phones, handheld messaging devices, laptop computers, set-top boxes,
personal data
assistants, electronic book readers and the like. The network can include any
appropriate network, including an intranet, the Internet, a cellular network,
a local area
network or any other such network or combination thereof. Components used for
such
a system can depend at least in part upon the type of network and/or
environment
selected. Protocols and components for communicating via such a network are
well
known and will not be discussed herein in detail. Communication over the
network can
be enabled via wired or wireless connections and combinations thereof. In this

example, the network includes the Internet, as the environment includes a Web
server
806 for receiving requests and serving content in response thereto, although
for other
networks an alternative device serving a similar purpose could be used, as
would be
apparent to one of ordinary skill in the art.
[0062] The illustrative environment includes at least one application server
808 and a
data store 810. Tt should be understood that there can be several application
servers,
layers or other elements, processes or components, which may be chained or
otherwise
configured, which can interact to perform tasks such as obtaining data from an

appropriate data store. As used herein the term "data store" refers to any
device or
combination of devices capable of storing, accessing and retrieving data,
which may
include any combination and number of data servers, databases, data storage
devices
and data storage media, in any standard, distributed or clustered environment.
The

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application server can include any appropriate hardware and software for
integrating
with the data store as needed to execute aspects of one or more applications
for the
client device and handling a majority of the data access and business logic
for an
application. The application server provides access control services in
cooperation with
the data store and is able to generate content such as text, graphics, audio
and/or video
to be transferred to the user, which may be served to the user by the Web
server in the
form of HTML, XML or another appropriate structured language in this example.
The
handling of all requests and responses, as well as the delivery of content
between the
client device 802 and the application server 808, can be handled by the Web
server 806.
It should be understood that the Web and application servers are not required
and are
merely example components, as structured code discussed herein can be executed
on
any appropriate device or host machine as discussed elsewhere herein.
100631 The data store 810 can include several separate data tables, databases
or other
data storage mechanisms and media for storing data relating to a particular
aspect. For
example, the data store illustrated includes mechanisms for storing production
data 812
and user information 816, which can be used to serve content for the
production side.
The data store also is shown to include a mechanism for storing log or session
data 814.
It should be understood that there can be many other aspects that may need to
be stored
in the data store, such as page image information and access rights
information, which
can be stored in any of the above listed mechanisms as appropriate or in
additional
mechanisms in the data store 810. The data store 810 is operable, through
logic
associated therewith, to receive instructions from the application server 808
and obtain,
update or otherwise process data in response thereto. In one example, a user
might
submit a search request for a certain type of element. In this case, the data
store might
access the user information to verify the identity of the user and can access
the catalog
detail information to obtain information about elements of that type. The
information
can then be returned to the user, such as in a results listing on a Web page
that the user is
able to view via a browser on the user device 802. Information for a
particular element
of interest can be viewed in a dedicated page or window of the browser.
[0064] Each server typically will include an operating system that provides
executable
program instructions for the general administration and operation of that
server and
typically will include computer-readable medium storing instructions that,
when
executed by a processor of the server, allow the server to perform its
intended functions.

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Suitable implementations for the operating system and general functionality of
the
servers are known or commercially available and are readily implemented by
persons
having ordinary skill in the art, particularly in light of the disclosure
herein.
[0065] The environment in one embodiment is a distributed computing
environment
utilizing several computer systems and components that arc interconnected via
communication links, using one or more computer networks or direct
connections.
However, it will be appreciated by those of ordinary skill in the art that
such a system
could operate equally well in a system having fewer or a greater number of
components
than are illustrated in FIG. 8. Thus, the depiction of the system 800 in FIG.
8 should be
taken as being illustrative in nature and not limiting to the scope of the
disclosure.
[0066] As discussed above, the various embodiments can be implemented in a
wide
variety of operating environments, which in some cases can include one or more
user
computers, computing devices, or processing devices which can be used to
operate any
of a number of applications. User or client devices can include any of a
number of
general purpose personal computers, such as desktop or laptop computers
running a
standard operating system, as well as cellular, wireless, and handheld devices
running
mobile software and capable of supporting a number of networking and messaging

protocols. Such a system also can include a number of workstations running any
of a
variety of commercially-available operating systems and other known
applications for
purposes such as development and database management. These devices also can
include other electronic devices, such as dummy terminals, thin-clients,
gaming
systems, and other devices capable of communicating via a network.
[0067] Various aspects also can be implemented as part of at least one service
or Web
service, such as may be part of a service-oriented architecture. Services such
as Web
services can communicate using any appropriate type of messaging, such as by
using
messages in extensible markup language (XML) format and exchanged using an
appropriate protocol such as SOAP (derived from the "Simple Object Access
Protocol").
Processes provided or executed by such services can be written in any
appropriate
language, such as the Web Services Description Language (WSDL). Using a
language
such as WSDL allows for functionality such as the automated generation of
client-side
code in various SOAP frameworks.

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100681 Most embodiments utilize at least one network that would be familiar to
those
skilled in the art for supporting communications using any of a variety of
commercially-
available protocols, such as TCP/IP, OSI, FTP, UPnP, NFS, CIFS, and AppleTalk.
The
network can be, for example, a local area network, a wide-area network, a
virtual
private network, the Internet, an intranet, an extranet, a public switched
telephone
network, an infrared network, a wireless network, and any combination thereof.
[0069] In embodiments utilizing a Web server, the Web server can run any of a
variety
of server or mid-tier applications, including HTTP servers, FTP servers, CGI
servers,
data servers, Java servers, and business application servers. The server(s)
also may be
capable of executing programs or scripts in response requests from user
devices, such as
by executing one or more Web applications that may be implemented as one or
more
scripts or programs written in any programming language, such as Java , C, C#
or
C++, or any scripting language, such as Perl, Python, or TCL, as well as
combinations
thereof. The server(s) may also include database servers, including without
limitation
those commercially available from Oracle , Microsoft , Sybasek, and IBM .
[0070] The environment can include a variety of data stores and other memory
and
storage media as discussed above. These can reside in a variety of locations,
such as on
a storage medium local to (and/or resident in) one or more of the computers or
remote
from any or all of the computers across the network. In a particular set of
embodiments,
the information may reside in a storage-area network ("SAN") familiar to those
skilled
in the art. Similarly, any necessary files for performing the functions
attributed to the
computers, servers, or other network devices may be stored locally and/or
remotely, as
appropriate. Where a system includes computerized devices, each such device
can
include hardware elements that may be electrically coupled via a bus, the
elements
including, for example, at least one central processing unit (CPU), at least
one input
device (e.g., a mouse, keyboard, controller, touch screen, or keypad), and at
least one
output device (e.g., a display device, printer, or speaker). Such a system may
also
include one or more storage devices, such as disk drives, optical storage
devices, and
solid-state storage devices such as random access memory ("RAM") or read-only
memory ("ROM"), as well as removable media devices, memory cards, flash cards,
etc.
[0071] Such devices also can include a computer-readable storage media reader,
a
communications device (e.g., a modem, a network card (wireless or wired), an
infrared
communication device, etc.), and working memory as described above. The
computer-

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readable storage media reader can be connected with, or configured to receive,
a
computer-readable storage medium, representing remote, local, fixed, and/or
removable
storage devices as well as storage media for temporarily and/or more
permanently
containing, storing, transmitting, and retrieving computer-readable
information. The
system and various devices also typically will include a number of software
applications, modules, services, or other elements located within at least one
working
memory device, including an operating system and application programs, such as
a
client application or Web browser. It should be appreciated that alternate
embodiments
may have numerous variations from that described above. For example,
customized
hardware might also be used and/or particular elements might be implemented in

hardware, software (including portable software, such as applets), or both.
Further,
connection to other computing devices such as network input/output devices may
be
employed.
[0072] Storage media and computer readable media for containing code, or
portions
of code, can include any appropriate media known or used in the art, including
storage
media and communication media, such as but not limited to volatile and non-
volatile,
removable and non-removable media implemented in any method or technology for
storage and/or transmission of information such as computer readable
instructions, data
structures, program modules, or other data, including RAM, ROM, EEPROM, flash
memory or other memory technology, CD-ROM, digital versatile disk (DVD) or
other
optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or
other
magnetic storage devices, or any other medium which can be used to store the
desired
information and which can be accessed by the a system device. Based on the
disclosure
and teachings provided herein, a person of ordinary skill in the art will
appreciate other
ways and/or methods to implement the various embodiments.
[0073] The specification and drawings are, accordingly, to be regarded in an
illustrative rather than a restrictive sense. It will, however, be evident
that various
modifications and changes may be made thereunto without departing from the
broader
spirit and scope of the invention as set forth in the claims.
[0074] Various embodiments of the disclosure can be described in view of the
following clauses:

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Al. A computer-implemented method for index configuration for
searchable data in a networked environment, comprising:
receiving data to be indexed, the data including a plurality of data fields;
determining a name associated with each data field in the plurality of
data fields;
determining a field type, of a plurality of field types, associated with
each data field in the plurality of data fields, the plurality of field types
including at least
one of an integer type, a literal type, or a text type;
determining whether to enable one or more search options for each of the
data fields, the one or more search options including at least one of an
option to include
a respective data field in a search index to be generated, an option to
calculate a facet
count for the respective data field, or an option to provide one or more
values associated
with the respective data field;
generating a search index configuration for the data based at least in part
on the field type of each data field included the data and the determining
whether to
enable the one or more search options; and
generating a search index for the data based at least in part on the search
index configuration for the data.
A2. The computer-implemented method of clause Al, wherein the
data is of a first format, further comprising:
converting the data from the first format to a second format, the second
format being compatible with the search index; and
storing the data converted to the second format on one or more storage
allocations.
A3. The computer-implemented method of clause A2, wherein the
converting the data from the first format to the second format comprises:
comparing the first format with the second format; and
modifying at least one data field associated with the first format to
correspond to at least one data field associated with the second format.
A4. The computer-implemented method of clause A2, wherein the
second format is a Search Data Format (SDF).

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A5. A computer-implemented method comprising:
receiving data to be indexed;
determining a type of a data field associated with the data, the type of the
data field being determined from a plurality of types of data fields;
determining one or more search options to be enabled with respect to the
data field associated with the data;
generating an index configuration for the data based at least in part on the
type of the data field and the one or more search options; and
generating a search index for the data based at least in part on the index
configuration for the data.
A6. The computer-implemented method of clause A5, wherein the
data is of a first format, further comprising:
converting the data from the first format to a second format, the second
format being compatible with the search index; and
storing the data converted to the second format on one or more storage
allocations.
A7. The computer-implemented method of clause A6, wherein the
converting the data from the first format to the second format comprises:
comparing the first format with the second format; and
modifying at least one data tag associated with the first format to
correspond to at least one data tag associated with the second format.
A8. The computer-implemented method of clause A5, wherein the
plurality of types of data fields includes at least one of an integer type, a
text type, a
literal type, a geolocation type, a time type, a date type, or a floating
point number type.
A9. The computer-implemented method of clause A8, wherein the
determining the type of the data field comprises:
determining that a value associated with the data field has an amount of
integer characters above a specified integer amount threshold; and
determining the type of the data field to be the integer type.

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A10. The computer-implemented method of clause A8, wherein the
determining the type of the data field comprises:
determining at least one of a value associated with the data field having
an amount of alphanumeric characters above a specified text amount threshold,
a
number of distinct values associated with the data field being above a
specified text
distinct amount threshold, a percentage of distinct values being above a
specified text
distinct percentage threshold, or a length of values being above a specified
text length
threshold; and
determining the type of the data field to be the text type.
All. The computer-implemented method of clause A8, wherein the
determining the type of the data field comprises:
determining at least one of a value associated with the data field having
an amount of alphabetic characters above a specified lower literal amount
threshold but
below a specified upper literal amount threshold, a number of distinct values
associated
with the data field being below a specified literal distinct amount threshold,
a
percentage of distinct values being below a specified literal distinct
percentage
threshold, or a length of values being below a specified literal length
threshold; and
determining the type of the data field to be the literal type.
Al2. The computer-implemented method of clause A5, wherein the
one or more search options include at least one of an option to include the
data field in
the search index to be generated, an option to calculate a facet count for the
data field,
or an option to provide a value associated with the data field in response to
a relevant
search query.
A13. The computer-implemented method of clause Al 2, wherein the
determining the one or more search options to be enabled comprises deciding to
enable
the option to include the data field in the search index to be generated, the
decision
being based at least in part on at least one of receiving a signal included in
the data field
indicating that the data field is to be included in the search index or
determining a type
of the data field to be a literal type.

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A14. The computer-implemented method of clause Al2, wherein the
determining the one or more search options to be enabled comprises deciding to
enable
the option to calculate the facet count for the data field, the decision being
based at least
in part on determining that a quantity for a distribution of a plurality of
values
associated with the data field is below a specified facet count upper
threshold.
A15. The computer-implemented method of clause Al2, wherein the
determining the one or more search options to be enabled comprises deciding to
enable
the option to provide the value associated with the data field in response to
the relevant
search query, the decision being based at least in part on at least one of
receiving a
signal included in the data field indicating that the value associated with
the data field is
to be provided or determining that a length of the value associated with the
data field is
below a specified return value length threshold.
A16. The computer-implemented method of clause A5, further
comprising:
providing at least one of the data, the index configuration, or the index to
be searchable by one or more search queries.
Al?. The computer-implemented method of clause A5, further
comprising:
modifying the index configuration based at least in part on one or more
user-initiated inputs.
A18. A system comprising:
at least one communications transceiver;
one or more storage allocations;
at least one processor; and
a memory device including instructions that, when executed by the at
least one processor, cause the system to:
receive, via the at least one communications transceiver, data to
be indexed;
determine a type of a data field associated with the data, the type
of the data field being determined from a plurality of types of data fields;

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determine one or more search options to be enabled with respect
to the data field associated with the data;
generate an index configuration for the data based at least in part
on the type of the data field and the one or more search options; and
generate a search index for the data based at least in part on the
index configuration for the data.
A19. The system of clause A18, wherein the data is of a first format,
and wherein the instructions cause the system to further:
convert the data from the first format to a second format, the second
format being compatible with the search index; and
store the data converted to the second format on the one or more storage
allocations.
A20. The system of clause A19, wherein the instructions cause the
system to convert the data from the first format to the second format based on

comparing the first format with the second format and modifying at least one
data field
associated with the first format to correspond to at least one data field
associated with
the second format.
A21. A non-transitory computer-readable storage medium including
instructions for identifying elements, the instructions when executed by a
processor of a
computing system causing the computing system to:
receive data to be indexed;
determine a type of a data field associated with the data, the type of the
data field being determined from a plurality of types of data fields;
determine one or more search options to be enabled with respect to the
data field associated with the data;
generate an index configuration for the data based at least in part on the
type of the data field and the one or more search options; and
generate a search index for the data based at least in part on the index
configuration for the data.

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A22. The non-transitory computer-readable storage medium of clause
A21, wherein the plurality of types of data fields includes at least one of an
integer type,
a text type, a literal type, a geolocation type, a time type, a date type, or
a floating point
number type.
A23. The non-transitory computer-readable storage medium of clauseA
22, wherein the instructions cause the computing system to determine the type
of the
data field to be the literal type based on determining at least one of a value
associated
with the data field having an amount of alphabetic characters above a
specified lower
literal amount threshold but below a specified upper literal amount threshold,
a number
of distinct values associated with the data field being below a specified
literal distinct
amount threshold, a percentage of distinct values being below a specified
literal distinct
percentage threshold, or a length of values being below a specified literal
length
threshold.
A24. The non-transitory computer-readable storage medium of clause
A21, wherein the one or more search options include at least one of an option
to include
the data field in the search index to be generated, an option to calculate a
facet count for
the data field, or an option to provide a value associated with the data field
in response
to a relevant search query.
A25. The non-transitory computer-readable storage medium of clauseA
24, wherein the determining the one or more search options to be enabled
comprises
deciding to enable the option to calculate the facet count for the data field,
the decision
being based at least in part on determining that a quantity for at least one
value
associated with the data field is above a specified facet count lower
threshold and below
a specified facet count upper threshold.
Bl.A computer-implemented method for dynamic search partitioning,
comprising:
monitoring at least one of an amount of data being stored or a rate at
which data is being manipulated on a first partition provided by a network
service, the
first partition being included in a storage allocation provided by the network
service;

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detecting that the at least one of the amount or the rate exceeds a
specified amount threshold or a specified rate threshold, respectively;
performing, in response to the detecting, at least one of an increase to a
size of the first partition or an addition of at least a second partition to
the storage
allocation, the at least one of the increase or the addition being based at
least in part on
the amount of data being stored or the rate at which data is being
manipulated;
directing network traffic associated with the storage allocation to a cache
provided by the network service during the at least one of the increase or the
addition;
and
directing the network traffic to the storage allocation when the
performing the at least one of the increase or the addition is complete.
B2. The computer-implemented method of clause Bl, further
comprising:
monitoring a search index for the storage allocation;
detecting that a size of the search index exceeds a specified index size
threshold; and
updating the search index for the storage allocation to reflect the at least
one of the increase or the addition with respect to the storage allocation.
B3. The computer-implemented method of clause Bl, wherein the
increase to the size of the first partition is performed if the size of the
first partition is
below a maximum partition size threshold, and wherein the addition of at least
the
second partition is performed if the size of the first partition is at the
maximum partition
size threshold.
B4. A computer-implemented method comprising:
monitoring data usage on a storage allocation in a networked
environment, the storage allocation having a number of partitions including at
least one
partition;
determining whether the data usage on the at least one partition included
in the storage allocation exceeds a specified threshold;
modifying at least one of a size of the at least one partition or the number
of partitions included in the storage allocation;

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directing network traffic associated with the storage allocation away
from a portion of the storage allocation associated with the modifying of the
at least one
of the size or the number; and
directing the network traffic to the portion of the storage allocation
associated with the modifying when the modifying is complete.
B5. Thc computer-implemented method of clause B4, further
comprising:
detecting that a size of a search index for the storage allocation exceeds a
specified index size threshold; and
updating the search index for the storage allocation based on the
modifying the at least one of the size of the at least one partition or the
number of
partitions included in the storage allocation.
B6. The computer-implemented method of clause B5, wherein the
updating the search index includes rebuilding the search index for the storage
allocation
to reflect the modifying the at least one of the size of the at least one
partition or the
number of partitions included in the storage allocation.
B7. The computer-implemented method of clause B4, wherein the
data usage includes at least one of an amount of data being stored on the
storage
allocation or a rate at which data is being manipulated on the storage
allocation.
B8. The computer-implemented method of clause B7, wherein the
specified threshold includes at least one of a specified amount threshold or a
specified
rate threshold, and wherein the data usage exceeds the specified threshold
when there is
an occurrence of at least one of the amount of data being stored exceeds the
specified
amount threshold or the rate at which data is being manipulated exceeds the
specified
rate threshold.
B9. The computer-implemented method of clause B8, wherein the
specified threshold is calculated based at least in part on information about
historical
data usage.

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B10. The computer-implemented method of clause B4, further
comprising:
determining that an amount of network traffic directed to the storage
allocation is above a specified traffic threshold; and
modifying the storage allocation based on the amount of network traffic.
B11. The computer-implemented method of clause B10, wherein the
network traffic includes search query traffic for searching data stored on the
storage
allocation.
B12. The computer-implemented method of clause B10, wherein the
modifying the storage allocation based on the amount of network traffic
includes at least
one of modifying the size of the at least one partition, modifying the number
of
partitions, or replacing at least one partition included in the number of
partitions with at
least one partition having different specifications.
B13. The computer-implemented method of clause B12, wherein the
different specifications include at least one of a different CPU power, a
different
capacity of RAM, a different capacity of hard disk space, or a different
capacity of
bandwidth.
B14. The computer-implemented method of clause B4, wherein the
modifying the at least one of the size of the at least one partition or the
number of
partitions includes increasing at least one of the size of the at least one
partition or the
number of partitions, wherein the increasing the size of the at least one
partition is
performed if the size of the at least one partition is below a maximum
partition size
threshold, and wherein the increasing the number of the partitions is
performed if the
size of the at least one partition is at the maximum partition size threshold
B15. The computer-implemented method of clause B4, wherein the
modifying the at least one of the size of the at least one partition or the
number of
partitions includes decreasing at least one of the size of the at least one
partition or the
number of partitions, wherein the decreasing the number of the partitions is
performed if
the number of the partitions is greater than one partition, and wherein the
decreasing the

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size of the at least one partition is performed if the number of the
partitions is one
partition.
B16. The computer-implemented method of clause B4, further
comprising:
determining a CPU usage of the storage allocation, wherein the
modifying the at least one of the size or the number is based on at least one
of the data
usage on the storage allocation or the determined CPU usage of the storage
allocation.
B17. The computer-implemented method of clause B4, further
comprising:
modifying a configuration of the storage allocation based on at least one
of a configuration associated with the data usage or a user-initiated input.
B18. The computer-implemented method of clause B4, further
comprising:
determining when to perform the modifying of the at least one of the size
or the number based on resources available to the storage allocation.
B19. A system comprising:
a storage allocation having a number of partitions including at least one
partition;
at least one processor; and
a memory device including instructions that, when executed by the at
least one processor, cause the system to:
monitor data usage on the storage allocation;
determine whether the data usage on the at least one partition
included in the storage allocation exceeds a specified threshold;
modify at least one of a size of the at least one partition or the
number of partitions included in the storage allocation;
direct network traffic associated with the storage allocation away
from a portion of the storage allocation associated with the modifying of the
at
least one of the size or the number; and

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direct the network traffic to the portion of the storage allocation
associated with the modifying when the modifying is complete.
B20. The system of clause B19, further comprising:
at least one load balancer configured to facilitate in the network traffic
being directed away from the portion of the storage allocation during the
modifying the
at least one of the size or the number and in the network traffic being
directed to the
portion of the storage allocation when the modifying the at least one of the
size or the
number is complete.
B21. The system of clause B20, wherein the at least one load balancer
is configured to direct the network traffic across the number of partitions
included in the
storage allocation.
B22. The system of clause B19, further comprising:
at least one monitor module configured to facilitate in the monitoring the
data usage on the storage allocation and in the determining whether the data
usage on
the at least one partition included in the storage allocation exceeds a
specified threshold.
B23. A non-transitory computer-readable storage medium including
instructions for identifying elements, the instructions when executed by a
processor of a
computing system causing the computing system to:
monitor data usage on a storage allocation in a networked environment,
the storage allocation having a number of partitions including at least one
partition;
determine whether the data usage on the at least one partition included in
the storage allocation exceeds a specified threshold;
modify at least one of a size of the at least one partition or the number of
partitions included in the storage allocation;
direct network traffic associated with the storage allocation away from a
portion of the storage allocation associated with the modifying of the at
least one of the
size or the number; and
direct the network traffic to the portion of the storage allocation
associated with the modifying when the modifying is complete.

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B24. The non-transitory computer-readable storage medium of clause
B23, wherein the instructions cause the computing system to further detect
that a size of
a search index for the storage allocation exceeds a specified index size
threshold and
update the search index for the storage allocation based on the modifying the
at least
one of the size of the at least one partition or the number of partitions
included in the
storage allocation.
B25. The non-transitory computer-readable storage medium of clause
B24, wherein the updating the search index includes rebuilding the search
index for the
storage allocation to reflect the modifying the at least one of the size of
the at least one
partition or the number of partitions included in the storage allocation.

Representative Drawing
A single figure which represents the drawing illustrating the invention.
Administrative Status

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Administrative Status

Title Date
Forecasted Issue Date 2018-03-27
(86) PCT Filing Date 2013-10-12
(87) PCT Publication Date 2014-04-17
(85) National Entry 2015-04-10
Examination Requested 2015-04-10
(45) Issued 2018-03-27

Abandonment History

There is no abandonment history.

Maintenance Fee

Last Payment of $263.14 was received on 2023-10-06


 Upcoming maintenance fee amounts

Description Date Amount
Next Payment if standard fee 2024-10-15 $347.00
Next Payment if small entity fee 2024-10-15 $125.00

Note : If the full payment has not been received on or before the date indicated, a further fee may be required which may be one of the following

  • the reinstatement fee;
  • the late payment fee; or
  • additional fee to reverse deemed expiry.

Patent fees are adjusted on the 1st of January every year. The amounts above are the current amounts if received by December 31 of the current year.
Please refer to the CIPO Patent Fees web page to see all current fee amounts.

Payment History

Fee Type Anniversary Year Due Date Amount Paid Paid Date
Request for Examination $800.00 2015-04-10
Application Fee $400.00 2015-04-10
Maintenance Fee - Application - New Act 2 2015-10-13 $100.00 2015-04-10
Maintenance Fee - Application - New Act 3 2016-10-12 $100.00 2016-09-20
Maintenance Fee - Application - New Act 4 2017-10-12 $100.00 2017-09-19
Final Fee $300.00 2018-02-09
Maintenance Fee - Patent - New Act 5 2018-10-12 $200.00 2018-10-08
Maintenance Fee - Patent - New Act 6 2019-10-15 $200.00 2019-10-04
Maintenance Fee - Patent - New Act 7 2020-10-13 $200.00 2020-10-02
Maintenance Fee - Patent - New Act 8 2021-10-12 $204.00 2021-10-11
Maintenance Fee - Patent - New Act 9 2022-10-12 $203.59 2022-10-07
Maintenance Fee - Patent - New Act 10 2023-10-12 $263.14 2023-10-06
Owners on Record

Note: Records showing the ownership history in alphabetical order.

Current Owners on Record
A9.COM, INC.
Past Owners on Record
None
Past Owners that do not appear in the "Owners on Record" listing will appear in other documentation within the application.
Documents

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Document
Description 
Date
(yyyy-mm-dd) 
Number of pages   Size of Image (KB) 
Abstract 2015-04-10 2 69
Claims 2015-04-10 3 112
Drawings 2015-04-10 7 159
Description 2015-04-10 33 1,642
Representative Drawing 2015-04-10 1 15
Cover Page 2015-04-30 2 45
Claims 2016-12-21 8 230
Drawings 2016-12-21 7 149
Description 2016-12-21 35 1,749
Examiner Requisition 2017-05-24 3 181
Amendment 2017-07-20 5 175
Description 2017-07-20 35 1,641
Abstract 2017-07-20 1 17
Final Fee 2018-02-09 2 69
Representative Drawing 2018-02-28 1 7
Cover Page 2018-02-28 2 47
Assignment 2015-04-10 3 92
PCT 2015-04-10 9 553
Examiner Requisition 2016-06-22 5 232
Amendment 2016-12-21 22 690