Note: Descriptions are shown in the official language in which they were submitted.
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SYSTEMS AND METHODS TO PROVIDE SEARCH BASED ON SOCIAL GRAPHS
AND AFFINITY GROUPS
BACKGROUND
Field
[0001] At least some embodiments of the disclosure relate generally to the
field of
information searches and, more particularly but not limited to, identifying
and presenting
relationship-based recommendations for searches.
Description of the Related Art
Some search tools allow a user to search using a search query. For example, a
user
may enter a location and a query for "Italian restaurants" to identify Italian
restaurants in
a specified area.
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BRIEF DESCRIPTION OF THE DRAWINGS
[0002] These and other features, aspects, and advantages will become better
understood with regard to the following description, appended claims, and
accompanying drawings where:
[0003] FIGURE 1 is a diagram of one embodiment of a system for performing a
search
method.
[0004] FIGURE 2 is a diagram of one embodiment of a relationship graph.
[0005] FIGURE 3 is a flow chart illustrating one embodiment of a method of a
search
method.
[0006] FIGURE 4 illustrates a screen display of one embodiment of a search
interface.
[0007] FIGURE 5 illustrates a screen display of another embodiment of a search
interface.
[0008] FIGURE 6 is a diagrammatic representation of an embodiment of a
machine,
within which a set of instructions for causing the machine to perform one or
more of the
methodologies discussed herein may be executed.
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DETAILED DESCRIPTION
[0009] The following description and drawings are illustrative and are not to
be
construed as limiting. Numerous specific details are described to provide a
thorough
understanding of the disclosure. However, in certain instances, well known or
conventional details are not described in order to avoid obscuring the
description.
References to one or an embodiment in the present disclosure can be, but not
necessarily are, references to the same embodiment; and, such references mean
at
least one.
[0010] Reference in this specification to "one embodiment" or "an embodiment"
means
that a particular feature, structure, or characteristic described in
connection with the
embodiment is included in at least one embodiment of the disclosure. The
appearances
of the phrase "in one embodiment" in various places in the specification are
not
necessarily all referring to the same embodiment, nor are separate or
alternative
embodiments mutually exclusive of other embodiments. Moreover, various
features are
described which may be exhibited by some embodiments and not by others.
Similarly,
various requirements are described which may be requirements for some
embodiments
but not other embodiments.
[0011] Embodiments of the disclosure includes methods, machine-readable media,
apparatuses and systems to identify and/or present information based on
relationship-
based recommendations. The information may be search results; and the
relationship-
based recommendations may be recommendations or preferences specified by
related
people in one or more social networks or affinity groups. For example, the
search
results can be presented in an order based at least in part on the
recommendations and
the relationship between the people who made the recommendations and the
person
who requested the search results.
[0012] FIGURE 1 is a diagram of one embodiment of a system for performing a
search
method.
[0013] In some embodiments, a search device (e.g., 100) aggregates
recommendations of businesses, service providers, products, information,
entertainment programs, merchants, etc., on one or more social networks (e.g.,
120,
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130, etc.), tracks the user identifications of those making the
recommendations on the
social networks (e.g., 120, 130, etc.) and retrieves the relationships between
user
identifications from the social networks. The search device also provides
search results
in response to a searching user's search query. The search device selects
businesses
that are most relevant based on the search query and the number of
recommendations
of each business from users that are most closely related to the searching
user. In
some embodiments, the search device counts only the number of recommending
users
of a predetermined degree of closeness to the searching user. The searching
user can
use the rank of the business in the search result, the number of recommending
users
and the identity of some or all of the recommending users to influence their
decision as
to which business to use. Generally speaking, the recommendations of more
closely
related recommending users are more relevant to a searching user than
recommendations of more distantly related or unrelated users.
[0014] In FIGURE 1, people use user devices (e.g., 140, 150) to connect to
services
through the internet (110). User devices (e.g., 140, 150) can take many forms
including
desktop and notebook computers, mobile phones, and personal digital assistants
(PDAs). In the illustrated embodiment, the user device 140 and the user device
150 are
configured to be connected through the internet 110 to the social network 120,
the
social network 130 and the search device 100.
[0015] The social network 120 and the social network 130 may take various
forms.
Social networks include online communities where users interact and establish
relationships with each other. Examples of social networks include the
FACEBOOK ,
MySpace and Linkedin web sites. (FACEBOOK, MySpace and Linkedin are
registered trademarks of Facebook, Inc., Myspace, Inc. and Linkedin
Corporation,
respectively.) Users of social networks (e.g., 140, 150) interact with each
other in
various ways including chat, email, file sharing, blogging, and affinity
groups. Affinity
groups may be groups that people join for any number of reasons such as to
express a
particular interest, engage in discussions about a particular subject or
express a
relationship with other members. Users of social networks establish
relationships with
each other in various ways on the social networks, including by joining common
affinity
groups, becoming "friends" or making a "connection."
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[0016] A person using a user device (e.g., 140, or 150) may log into a social
network
(e.g., 120 or 130) to interact and establish relationships with other users.
In some
cases, the same person may access the social networks using different user
devices at
different times. For example, the person may use their desktop computer when
at work,
their laptop computer in a meeting, and their mobile phone when on the road.
In each
case, the person is identified to the social network by using a user
identification to log
into the social network from one of the user devices. In some cases, the user
may use
the user device 140 to concurrently log into both the social network 120 and
the social
network 130.
[0017] A first person may use the user device 140 to connect through the
internet 110
to the social network 120. A second person may use the user device 150 to
connect
through the internet 110 to the social network 120. The first person may
interact and
become friends with the second person on the social network 120. Similarly,
the first
and second person may also interact and become friends on the social network
130.
[0018] In some embodiments, users log into a social network or their user
device using
a user identification and password. In some cases, the user is somewhat
anonymous in
that the user identification is a user name or screen name. In other cases,
the user
identification may be associated with more specific identifying information,
such as the
user's real name or social security number. In some embodiments, a person is
identified by different user names depending on which social network or user
device
they are accessing. In such embodiments, the search device may associate a
common
user identification with each of the user names so that information associated
with this
person may be aggregated across multiple information sources.
[0019] The first person may click on a widget in a web page on the social
network 120
to indicate that the user prefers or recommends a first business. The widget
is a
mechanism for allowing the user to interact with the social network 120. For
example,
the widget may be a button, checkbox, or drop down list in a web page on the
social
network 120. The second person may click a widget in a web page on the social
network 120 that indicates that the user prefers or recommends the first
business as
well. The second person may recommend a second business instead of or in
addition
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to the first business. Similarly, other users may indicate preferences for one
or more
businesses on the social network 120 and the social network 130. Furthermore,
these
users may interact similarly with other social networks.
[0020] The context and processes for indicating these preferences and
recommendations may be implemented in any of a number of ways on each of these
social networks. For example, a user may browse a list of businesses from a
database
and click on a widget associated with a particular business to indicate a
preference. In
other cases, a user may review the recommended businesses of other users and
click
on a widget to adopt a particular recommendation as their own.
[0021] In some cases, a user may log into an account managed by the search
device
100 using a user identification and make recommendations directly associated
with the
user profile maintained by the search device 100. For example, the user may
visit the
web site of a business and click on a button on their browser to add that
business to
their recommended businesses as stored in their account on the search device.
In
other cases, the user logs into the social network using a user identification
and makes
the recommendations within the context of that social network. The search
device 100
subsequently retrieves this information from the social network and associates
the
information with the user profile maintained by the search device.
[0022] In some embodiments, users of the social networks recommend businesses
by
clicking on a widget associated with a particular business to indicate that
the user
prefers or recommends that business. These recommendations and preferences may
be available to other users in various ways including by viewing the
recommending
user's profile on the social network or receiving announcements of new
recommendations through a messaging feature of the social network. The social
network may employ other methods of indicating and sharing a preference or
recommendation for certain businesses.
[0023] In some embodiments, users select one of several levels of favorites to
indicate
the strength of a recommendation. For example, user may click on one of two
buttons
to indicate that a particular business is either "recommended" or "highly
recommended."
In other cases, a multiple point scale may be used to indicate the strength of
the
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recommendation. Other methods for users to indicate a preference for a certain
business may be used. In some embodiments, these recommended businesses may
be listed in the favorite list in the profile of the user on the social
network or internet site
[0024] In the illustrated embodiment, the search device 100 is coupled through
the
internet 110 to the social network 120 and the social network 130. The search
device
100 includes one or more computers configured to perform the functionality
described
herein. For example, the search device may include one or more computers to
implement web server functionality to interface with the user devices 140 and
150 and
social networks 120 and 130 over the internet. Furthermore, the search device
may
include one or more databases configured to manage information including user
profiles
and recommended businesses and configured to search that information in
response to
search queries. The databases are configured to store multiple relationships
between
user identifications, a list of favorite businesses of each user
identification, and
relationships between each user identification and an affinity group or social
network.
[0025] The search device 100 interacts with the social networks 120 and 130
and
aggregates recommended businesses and user identifications of people that
recommend each recommended business on the social networks. The search device
100 also retrieves one or more relationship graphs (e.g., 210 illustrated in
FIGURE 2)
from the social network 120 and the social network 130. The relationship
graphs
include information about the relationships between user identifications on
the social
networks. For example, the relationship graph may include information about
which
users are members of each affinity groups, which users are directly related as
friends or
connections, and which users are more remotely connected through intermediate
friends or connections, such as a friend of a friend.
[0026] In some cases, the user identifications are the login identifier for
each social
network. The social network 110 may maintain a relationship graph indicating
the
relationships of each user based on a unique user identification (for example,
login id)
for those users on the social network 110 and the social network 120 may
maintain a
relationship graph indicating the relationships of each user based on the
unique user
identification for those users on the social network 120. In many cases, a
particular
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person's login id for one social network will not be the same on another
social network.
In some embodiments, the user identifications known to be associated with the
same
person (aliases) in different social networks are associated each other to
allow the
relationship graphs from several social networks to be merged at least
partially based
on the known aliases. In some cases, the search device 100 independently uses
each
relationship graph for each social network based on the internally unique user
identifications within each social network. In other cases, the search device
100 uses a
merged relationship graph based on the internally unique user identifications
within
each social network and aliases across social networks.
[0027] The user device 140 and the user device 150 are also connected over the
internet 110 to the search device 100. Persons can submit business search
queries on
their user devices. For example, a person wanting to find someone to fix their
Porche,
may submit a search query "Porsche mechanic" to the user device 140 using a
keyboard or voice input, for example. The user device 140 submits the search
query
over the internet 110 to the search device 100. In some cases, a location of
the
searching user is provided to the search device 140 so that the search service
can
prioritize relevant businesses based at least in part by distance from the
searching user.
The search device 100 provides the search results over the internet to the
user device
140 to the searching user.
[0028] In some embodiments, the search device 100 selects businesses in
response
to a search query based at least in part on the number of recommendations of
each
business by recommending users of a certain degree of closeness to the
searching user
in the one or more relationship graphs. For example, the search device 100 may
select
and rank businesses based at least in part on the number of recommendations
from
recommending users with a direct relationship with the searching user. In
other cases,
the search device 100 counts users with recommendations from recommending
users
with second degree, third degree and higher degree relationships with the
searching
user and ranks the businesses at least in part based on these counts.
[0029] In some embodiments, the search device 100 counts only recommendations
from users in certain affinity groups or particular social networks. For
example, if the
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searching user is searching for a financial advisor, the searching user might
only be
interested in the recommendations of people in a selected affinity group. In
some
cases, the user specifies a particular affinity group or social network to
include based for
example on their perception of the relevant expertise of members of that group
or
network. In other cases, the selection of groups or networks to include is
done
automatically based on the search query. For example, the search device 100
may only
count relationships within finance related groups if the search device 100
determines
that the search query is related to a finance related matter.
[0030] In some embodiments, the search device 100 transmits the search results
over
the internet 110 to the user device 140. The user device 140 presents the
search
results with an indication of one or more numbers of recommendations according
to one
or more criteria. In some cases, the one or more number of recommendations may
include the number of recommendations overall. In some cases, one or more
numbers
of recommendations are presented for one or more particular categories, such
as
number of recommendations among each of the searching user's first degree
relationships, second degree relationships, and third degree relationships.
Other
categories may include the number of recommending users that are a member of a
particular affinity group or a member of a particular social network.
[0031] The user device 140 also presents the search results with an indication
of one
or more user identifications associated with recommendations. In some cases,
all the
user identifications associated with the recommended business are presented.
The
search results may include user identifications selected or prioritized based
on the
recommending user's relevance to the searching user. In some embodiments, the
most
relevant users may be recommending users with the closest relationships to the
searching user. The closest relationships are ones which the searching user
may
recognize and find most persuasive in influencing their selection of one of
the presented
businesses. In some embodiments, the relevance of recommending users may be
based on one or more factors including the degree of closeness of the
relationship
between the two user identifications, the number of independent relationships
connecting the two user identifications, the number of common group
memberships,
and the relevance of each affinity group to the search query.
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[0032] In some embodiments, the search query is submitted to the search device
by
an application in a social network. For example, users of a social network may
load a
social network application to provide for business search queries in their
social network
profile, provide a mechanism for the user to identify and share favorite
businesses on
that social network and also allow the search device to access that user's
favorite
businesses and relationships on that social network.
[0033] In other embodiments, the search query is submitted through an
application
programming interface (API) to the search device. For example, the API may
provide
for business search queries in their social network profile, provide a
mechanism for the
user to identify and share favorite businesses on that website and also allow
the search
device to access that user's favorite businesses and relationships on that
website. In
some cases, the search results not only includes the recommendations from
recommending users in the network of the searching user, but also
recommendations
from recommending users associated with the website incorporating the API.
[0034] For example, an API as incorporated in a newspaper website may allow
the
search device to aggregate the business recommendations of the newspaper
website
users. The search device can then include the newspaper website user
recommendations in search results provided to the newspaper website. A product
review website may incorporate the API to include the recommendations of users
of the
product review website.
[0035] In some embodiments, the search device 100 aggregates recommendations
of
all users of the website. In other embodiments, the API can be configured to
specify
that recommendations from a specific subset of users on the website are
included. For
example, the search device 100 might aggregate the recommendations of
newspaper
editors on the newspaper website and aggregate the recommendations of product
review staff on the product review website.
[0036] In some cases, the recommendations of these the users associated with
the
website are incorporated into the search results on the website for all
searches. In
other embodiments, the recommendations of these us are only incorporated into
certain
types of searches, such as search queries related to their area of expertise.
For
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example, only restaurant recommendations of the restaurant critics on the
newspaper
website might be incorporated into the search results.
[0037] FIGURE 2 shows a graphical representation of one embodiment of two
relationship graphs. The relationship graphs are described with reference to
FIGURE 1.
[0038] A graph 210 represents a portion of the relationship information that
the search
device 100 receives from the social network 120 and a graph 220 represents a
portion
of the relationship that the search engine receives from the social network
130. The
relationship graphs are simplified in order to more clearly illustrate the
concept. In some
embodiments, there are millions of user identifications interconnected in each
relationship graph.
[0039] On the graph 210, a user identification (UI) 201 is connected to a UI
203 and
the UI 203 is connected to a UI 202. In some embodiments, these connections
may be
established in response to people associated with a pair of user
identifications
becoming "friends," making a connection or joining a common affinity group,
for
example, on the social network 120. In some embodiments, the connections
between
user identifications on the graphs include information about the types and
number of
relationships between the corresponding user identifications.
[0040] On the graph 220, a UI 208, being connected to a UI 207 directly, has a
first
degree relationship with the UI 207. The UI 208, being connected to a UI 206
through
the UI 207, has a second degree relationship with the UI 206. The UI 208,
being
connected to a UI 204 through the UI 207 and the UI 206, has a third degree
relationship with a UI 204. Higher order relationships between two user
identifications
include additional intermediate relationships between the user
identifications.
[0041] In some embodiments, the search device 100 independently uses the
relationship graphs (e.g., 210, 220) received from each social network (e.g.,
120, 130)
to carry out a method as described herein. In other embodiments, the search
device
100 merges the relationship graphs from different social networks (e.g., 120,
130)
based on aliases of user identifications provided to the search device 100.
More than
one user identification (aliases) may be associated with the same person on
one or
more social networks. For example, a person may use the UI 203 for the social
network
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120 and the UI 204 for the social network 130. When the person registers with
the
search device 100, the person may indicate the user identifications the person
uses on
each of one or more social networks (e.g., 120, 130). The search device 100
may
create a UI 205 to associate with or replace both the UI 203 and the UI 204 in
the
relationship graph used by the search device 100. In addition, the search
device 100
may merge the graph 210 and the graph 220 by associating user identifications
that the
search device 100 determines is associated with the same person. For example,
if the
search device determines that UI 203 is associated with the same person as UI
204,
then the graph 210 and the graph 220 can be merged by combining UI 203 and UI
204
into UI 205. This merged graph can lead to additional relationships between
graphs.
For example, if graph 210 is merged with graph 220 at U1205, U1206 has a
second
degree relationship with UI 201 even though the user identifications are
initially received
from different social networks.
[0042] In some embodiments, the search device 100 may receive only a portion
of the
relationship information available to the social networks due to privacy
controls and
other access restrictions for each social network. For example, the social
network 120
may only allow the search device 100 to retrieve the direct relationships
(e.g., friends
list) of registered users that grant access to the search device 100. In other
cases, the
social network grants access to user identifications of second, third and
higher degree
relationships of the registered users. Users of the social network may become
a
registered user of the search device 100 and grant access to the search device
100 by
loading an application on the social network 120 that enables such access.
[0043] In some embodiments, registered users submit profile information on
their user
device and the user device submits that profile information to the search
device 100.
The profile information may include one or more user identifications
associated with that
person on one or more social networks. The search device 100 may use that
information to access the portions of the relationship graphs available for
that user from
the social networks and merge the relationship graphs from two or more social
networks
based on aliases for that person across the social networks (e.g., 120, 130).
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[0044] In some embodiments, the social network (e.g., 120 or 130) and the
application
allow for the users to control what information is provided to the search
device 100.
Each social network may have independent restrictions that control
accessibility of the
relationship information by the search device 100. Furthermore, the search
device 100
may not merge user identifications across different social graphs because the
search
device 100 may not receive information about all the user identifications that
are
associated with the same person.
[0045] In other embodiments, the relationship graphs may be represented in
other
ways and incorporate other relationship information.
[0046] FIGURE 3 shows a flow chart of one embodiment of a search method. In
some
embodiments, the process is implemented in a system as illustrated in FIGURE
1.
However other general or special purpose apparatus and systems may be used to
carry
out a process contemplated to be within the spirit and scope of this
disclosure.
[0047] In process 300, a search device 110 aggregates preferred or recommended
businesses and associated user identifications of the persons recommending
each
business. In one embodiment, the search device 110 is communicatively coupled
to
one or more sources of preferred or recommended businesses, such as a social
network (e.g., 120 or 130) or a browser running on a user device (e.g., 140 or
150).
[0048] In some embodiments, the search device 110 aggregates favorite
businesses
and associated user identifications by interfacing with the social networks
(e.g., 120 or
130) through an application programming interface (API). In some embodiments,
the
search device aggregates favorite businesses and associated user
identifications by
interfacing with a user device running a browser with a browser plug-in. A
user may
visit a website of a business using the browser and click on a widget to
identify that
business as a favorite business. In some embodiments, the user device (e.g.,
140 or
150) transmits the business and a user identification to the search device
(100). In
other embodiments, the user device saves that favorite business locally on the
user
device to be retrieved by the search device at a later time. In some
embodiments, the
user identification is the login identification specified by logging into the
search device
using the browser plug in.
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[0049] In other embodiments, the search device 100 aggregates favorite
businesses
and associated user identifications by screen scraping, data extraction and
other
methods of mining information from sources such as data files and web pages.
[0050] In process 310, the search device 100 receives one or more relationship
graphs (e.g., 210, 220) to indicate the relationship between user
identifications. The
various social networks (e.g., 120, 130) and other sources of preferred or
recommended
businesses are accessed to receive a relationship graph indicating the
relationships
between the user identifications on that social network or other source of
preferred or
recommended businesses.
[0051] In some embodiments, the relationship graph (e.g., 210, 220) received
by the
search device 100 represents only a portion of the relationship information on
the social
network (e.g., 120 or 130) due to privacy restrictions limiting access to some
user
identifications and relationships on that social network. In some embodiments,
the
search device may only have access to the user identifications most closely
connected
to users granting access to the search device. Furthermore, in some
embodiments, the
degree of accessibility of user identifications associated with a specific
user
identification may depend on privacy configuration settings for that specific
user. In
addition, a user identification can be association with different user names
for each of
several sources of favorite businesses so that the relationship graphs for
each of those
several sources can be merged.
[0052] The user identifications may be user names, screen names, real names,
or
social security numbers, for example. In some embodiments, relationships are
established by being members of a common affinity group. For example, the
relationship graph may indicate two user identifications are associated with
each other
as members of a common FACEBOOK group. Furthermore, the relationship graph may
indicate two user identifications are associated with each other because they
established a connection with each other on Linkedin or became "friends" with
each
other on MySpace. In some cases, the relationship graph may indicate
relationships of
two or more degrees by tracking user identification relationships through one
or more
intermediate user identifications.
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[0053] In process 320, the search device 100 searches one or more databases to
select businesses based on the associated user identification and the one or
more
relationship graphs. In one embodiment, the search device receives a search
query
and selects businesses most relevant to the search query based on keyword
matching,
semantic matching, popularity ranking, concept matching or other methods of
using a
search query to select businesses.
[0054] In some embodiments, the database contains only preferred or
recommended
businesses having at least one associated user identification. Each associated
user
identification corresponds to a person that indicated a preference or
recommendation
for the corresponding business. In other embodiments, the database also
includes
businesses that do not have an associated user identification.
[0055] In some embodiments, the search device 100 selects businesses at least
in
part based on the number of associated user identifications in the database.
In some
cases, the search device selects only businesses with a predetermined minimum
number of associated user identifications or the highest number of user
identifications in
the database. Alternatively, the search device selects 100 only the most
relevant
relationships to the searching user. For example, the search device may count
those
associated user identifications within a predetermined maximum degree of
closeness
between the user identification of the recommending users and the searching
users.
[0056] In some cases, closeness may also be based on the number of independent
relationships between two users. For example, two users may be directly
related
though a friendship. These two users may be considered to have a closer
relationship
when they are also members of the same group as compared to two users that do
not
share a common group. Furthermore two users that share multiple common groups
and have friendships or connections on multiple sites or social networks may
be
considered to be closer than those that have fewer connections.
[0057] In some cases, the search device 100 selects the businesses using a
database
query that incorporates a search string related to identifying relevant
businesses, the
associated user identifications to indicate the number of recommendations and
the
relationship of the recommending users to the searching user according to one
or more
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relationship graphs. In other embodiments, the search device selects the
businesses
used two or more steps including a database search to identify relevant
businesses and
one or more filtering processes to extract only those businesses that meet
certain other
qualifications. These qualifications may include having a minimum number of
user
recommendations overall, having a minimum number of recommendations from
recommending users within a maximum degree of closeness to the searching user,
and
having a minimum number of recommendations from recommendations within one or
more selected affinity groups. Other single or multi-step processes may be
used to
identify selected businesses may be used.
[0058] In process 330, the search device 100 ranks the selected businesses
based on
the associated user identification and the one or more relationship graphs. In
one
embodiment, the search device receives a search query and selects businesses
most
relevant to the query and ranks them according to the number of associated
user
identifications within a maximum degree of closeness with the searching user.
[0059] In process 340, the search device 100 provides the search result
including one
or more selected businesses and associated user identifications in the ranked
order. In
one embodiment, the search device provides the search result over a network,
such as
the internet, to the user device of the searching user. In other embodiments,
the user
device provides the one or more selected businesses and associated user
identifications in ranked order to a display. In yet other embodiments, the
user device
provides the one or more selected businesses and associated user
identifications in
ranked order to a text-to-speech device to present the information in audio
form. Other
methods of providing the search result to a searching user may be used.
[0060] FIGURE 4 illustrates a screen display of a business search interface
according
to one embodiment. The screen display represents a display of business search
interface on a computer, PDA, or mobile telephone, for example.
[0061] A search query 400 is submitted, by a user device (e.g., 140 or 150) to
a
search device 100, in a field on the display. In some embodiments, the search
query
400 includes a text string like "coffee" to be used to identify businesses
relevant to the
searching user's need or want. The search device may use the search query 400
for
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keyword matching, semantic matching, concept matching or other ways to
identify the
most relevant businesses within a database. For example, "coffee shops" may be
identified through simply matching the keyword "coffee" from the search query
with the
names and descriptions of businesses in the database. In some cases, synonyms
may
be recognized such as "Java" and in other cases more sophisticated search
techniques
are used.
[0062] In some embodiments, the search query 400 also includes a location,
such as
"San Francisco, CA" or "SF, CA". The location is used to select or prioritize
businesses
in part based on how close the business is to this location. In other
embodiments, a
default location from the searching user's profile is used when a location is
not specified
in the search query. In yet other embodiments, the location of the user device
(e.g., 140
or 150) is submitted with the search query. The location of the user device
may be
automatically determined using a global positioning system (GPS) or other
position
determining apparatus integrated into or communicatively coupled with the user
device.
[0063] A tag cloud 405 displays tags related to the search query 400. The tag
cloud
405 may include related search terms most frequently used in previous search
queries
that included one or more terms in the search query 400. The size of the
related search
term may relate to the relative frequency of that term in previous search
queries using at
least one term in the search query 400. In one embodiment, clicking on a
related
search term in the tag cloud 405 modifies the search query 400 to include the
related
search term. A new tag cloud may be produced based on the modified search
query.
[0064] A selector 410 and a selector 420 is a widget on the page that allows
the user
to select which categories of recommendations should be counted to present a
ranked
list of recommended businesses.
[0065] If selector 410 is clicked, all recommendations in the searching user's
network
are counted. In one embodiment, the user's network includes all recommending
users
having a first, second or third degree relationship with the searching user in
one or more
relationship graphs. In other embodiments, the user's network may be more or
less
restrictive in terms of the closeness of the relationships included. The
user's network
may be defined in other ways. If selector 420 is clicked, all recommendations
in the
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entire network are counted. In one embodiment, the entire network may include
all
recommendations by all recommending users as aggregated by the search device.
Additional selectors may be used to predefine different categories of
recommendations
to count to determine the ranking of selected businesses.
[0066] A business 420 includes information associated with a recommended
business
listed first in the ranked list of businesses and a business 425 includes
information
associated with a recommended business listed second in the ranked list of
businesses.
The information associated with each business includes the business name,
address,
phone number, universal resource locator (URL), email address and other
details.
Graph counts 430, content 440 and widgets 451, 452, 453 and 454 are associated
with
the business 420 in the ranked list. Graph counts 435, content 445 and widgets
461,
462, 463 and 464 are associated with the business 425 in the ranked list.
Additional
businesses are listed in the ranked list of businesses.
[0067] In the illustrated embodiment, the graph counts identify the number of
recommending users with one degree relationships, with one or two degree
relationships, and with one, two or three degree relationships with the
searching user.
For example, graph counts 430 indicates that the business 420 has 361
recommending
users that have first degree (direct) relationships with the searching user,
500+
recommending users that have first or second degree relationships with the
searching
user and 3000+ recommending users that have first, second or third degree
relationships with the searching user.
[0068] Content may be associated with the recommended business that is
retrieved
from the social network or other sources. This content may be user submitted
reviews,
videos, photos and other information. In some cases, the content may be
submitted or
otherwise associated with one of the recommending users. For example, the
content
440 may be submitted by recommended users counted in the graph 430 and
associated
with the business 420.
[0069] Widget 451 allows the user to add the business 420 as a recommended
business associated with their user identification. In some cases, the user
identification
is one associated with the users profile on the search device. Widget 452
sends the
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business 420 to their mobile telephone using SMS messaging, for example.
Widget
454 sends the business 420 to their email address. Widget 453 sends the
business 420
to their friends as determined by the one or more relationship graphs.
[0070] FIGURE 5 illustrates a screen display of a business search interface
according
to another embodiment.
[0071] The graph counts 530 displays some or all of the user identifications
of
recommending users that recommended the business identified in a business 520.
In
some embodiments, the businesses are ranked by one or more of the different
categories of user identifications as described with reference to FIGURE 4. In
some
embodiments, the graph count 530 includes user identifications of some or all
of the
recommending users for the corresponding business. In some embodiments, only a
portion of the user identifications counted in the ranking of each business is
listed. In
one embodiment, the search device selects which user identifications to
present based
on the closeness of the relationship to the searching user using on one or
more
relationship graphs.
[0072] The searching user may be influenced to choose a specific one of the
selected
businesses based on its rank position but also based on the credibility that
the
searching user attributes to the users indicated by the displayed user
identifications.
Although the business 525 is ranked below the business 520, the user may
attribute
more credibility to the recommendation of the associated user identifications
in the
graph counts 530 than the recommendation of the associated user
identifications in the
graph counts 535. The searching user may chose a lower ranked selected
business
over a higher ranked selected business based on the identity of one or more
recommending users.
[0073] FIGURE 6 is a diagrammatic representation of an embodiment of a machine
600, within which a set of instructions for causing the machine to perform one
or more
of the methodologies discussed herein may be executed. The machine may be
connected (e.g., networked) to other machines. In a networked deployment, the
machine may operate in the capacity of a server or a client machine in a
client-server
network environment, or as a peer machine in a peer-to-peer (or distributed)
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environment. In one embodiment, the machine communicates with the server to
facilitate operations of the server and/or to access the operations of the
server.
[0074] In some embodiments, the machine 600 is a search device 100 according
to an
embodiment as described herein. In other embodiments, the machine 600 is a
component of the search device 100, such as one or more computers within the
search
device 100. In other embodiments, the machine 600 is a user device (e.g., 140,
150)
according to an embodiment as described herein. In one embodiment, the machine
600
is a portion of a social network (e.g., 120, or 130).
[0075] The machine 600 includes a processor 602 (e.g., a central processing
unit
(CPU) a graphics processing unit (GPU) or both), a main memory 604 and a
nonvolatile
memory 606, which communicate with each other via a bus 608. In some
embodiments, the machine 600 may be a desktop computer, a laptop computer,
personal digital assistant (PDA) or mobile phone, for example. In one
embodiment, the
machine 600 also includes a video display 610, an alphanumeric input device
612 (e.g.,
a keyboard), a cursor control device 614 (e.g., a mouse), a drive unit 616, a
signal
generation device 618 (e.g., a speaker) and a network interface device 620.
[0076] In one embodiment, the video display 610 includes a touch sensitive
screen for
user input. In one embodiment, the touch sensitive screen is used instead of a
keyboard and mouse. The disk drive unit 616 includes a machine-readable medium
622 on which is stored one or more sets of instructions 624 (e.g., software)
embodying
any one or more of the methodologies or functions described herein. The
instructions
624 may also reside, completely or at least partially, within the main memory
604 and/or
within the processor 602 during execution thereof by the computer system 600,
the
main memory 604 and the processor 602 also including machine-readable media.
The
instructions 624 may further be transmitted or received over a network 640 via
the
network interface device 620. In some embodiments, the machine-readable medium
622 also includes a database 625 including the aggregated businesses,
associated user
identifications and relationship graphs.
[0077] While the machine-readable medium 622 is shown in an exemplary
embodiment to be a single medium, the term "machine-readable medium" should be
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taken to include a single medium or multiple media (e.g., a centralized or
distributed
database, and/or associated caches and servers) that store the one or more
sets of
instructions. The term "machine-readable medium" shall also be taken to
include any
medium that is capable of storing, encoding or carrying a set of instructions
for
execution by the machine and that cause the machine to perform any one or more
of
the methodologies of the present disclosure. The term "machine-readable
medium"
shall accordingly be taken to include, but not be limited to, solid-state
memories, optical
and magnetic media, and carrier wave signals.
[0078] In general, the routines executed to implement the embodiments of the
disclosure, may be implemented as part of an operating system or a specific
application, component, program, object, module or sequence of instructions
referred to
as "programs." For example, one or more programs may be used to execute
specific
processes described herein. The programs typically comprise one or more
instructions
set at various times in various memory and storage devices in the machine, and
that,
when read and executed by one or more processors, cause the machine to perform
operations to execute elements involving the various aspects of the
disclosure.
[0079] Moreover, while embodiments have been described in the context of fully
machines, those skilled in the art will appreciate that the various
embodiments are
capable of being distributed as a program product in a variety of forms, and
that the
disclosure applies equally regardless of the particular type of machine or
computer-
readable media used to actually effect the distribution. Examples of machine-
readable
media include but are not limited to recordable type media such as volatile
and non-
volatile memory devices, floppy and other removable disks, hard disk drives,
optical
disks (e.g., Compact Disk Read-Only Memory (CD ROMS), Digital Versatile Disks,
(DVDs), etc.), among others, and transmission type media such as digital and
analog
communication links.
[0080] Although embodiments have been described with reference to specific
exemplary embodiments, it will be evident that the various modification and
changes
can be made to these embodiments. Accordingly, the specification and drawings
are to
be regarded in an illustrative sense rather than in a restrictive sense. The
foregoing
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specification provides a description with reference to specific exemplary
embodiments.
It will be evident that various modifications may be made thereto without
departing from
the broader spirit and scope as set forth in the following claims. The
specification and
drawings are, accordingly, to be regarded in an illustrative sense rather than
a
restrictive sense.
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