Note: Descriptions are shown in the official language in which they were submitted.
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
1
RECOMMENDATION ENGINE FOR INTERACTIVE SEARCH FORMS
BACKGROUND
The present invention relates to computers and computer software and, more
specifically, to systems, methods, and computer program products for providing
recommendations in an interactive travel-related search form.
Computer reservations systems are used to store and retrieve information and
to
conduct transactions related to air travel. A computer reservation system may
be used for
making the reservations of a particular airline. Alternatively, a computer
reservation system may
comprise a global distribution system that supports travel agencies and other
distribution
channels in making reservations for multiple airlines in a unified system.
Passenger travel may
be booked using the computer reservation system.
As a prerequisite to making a reservation, a prospective traveler or a travel
agent may
submit a travel search query to a server of the computer reservation system
using an online
application on a client device. The most common mechanism for submitting a
travel search
query requires a user to enter values into the controls of a form residing on
the client device.
The data may include search terms such as origin and destinations for a trip,
departure and return
dates for the trip, etc. A conventional approach for submitting the travel
search query is to enter
search terms as values into the controls of the form. The entered data is
transmitted to a server
of the computer reservation system, which performs a search based upon the
entered data and
returns matching itineraries to the client device for presentation to the
user.
WO 2001/80177 A2 discloses a search engine and data management technology that
can understand what users are looking for, understand the data in a database,
and present
immediately useful suggestions for finding the right information. Executable
suggestions, also
referred to as "Smart Tips", are disclosed that enable a user to further
narrow or broaden a search
intelligently and adaptively in real-time. Smart Tips describes a search and
corresponding search
criteria and provides information on the actual search results a user will
obtain according to these
search criteria. The system has a suggestion engine and one or more suggestion
spaces. There are
various form of Smart Tips: Static Smart Tips are simply static text messages
that always appear
on certain pages in the site. Dynamic Smart Tips are tips that appear based on
some action the
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
2
user has taken on the site, or related to where the user is on the site or
what they are trying to
accomplish. It is not the actual text of a Dynamic Smart Tip that is dynamic,
but the time and
location these tips appear. Static or Dynamic Smart Tips are, for example,
used while a user is
filling out a form such as a professional profile, a job posting, etc. The
system of WO
2001/80177 A2 then presents Static or Dynamic Smart Tips to help ensure that
the forms are
completed correctly, or to help encourage the user to fill out certain fields
completely or with
suggested content.
Improved systems, methods, and computer program products are needed to assist
the
user of an interactive travel search form when entering a travel-related
search query.
SUMMARY
According to an embodiment of the present invention, a method is provided for
interacting with an interactive form. The method may include receiving at a
server a value of a
first control of an interactive form, and applying at the server, a
recommendation rule that
interrelates the first control and a second control of the interactive form to
determine at least one
recommended value for the second control, wherein the second control is
unfilled when the value
of the first control is received at the server, and the at least one
recommended value represents
another portion of the travel-related search query. The method may further
include
communicating the at least one recommended value for the second control of the
interactive
form from the server to a client device and the client device transmitting the
travel-related search
query The first control and the second control, respectively, are one of a
button, a slider, a
spinner, a list box, a drop-down list and a combo box. The method may be
embodied in a
computer program product.
According to another embodiment of the present invention, a method is provided
for
interacting at a client device with an interactive form. The method receiving
at the client device
a value input into a first control of the interactive form and, in response to
receipt of the value of
the first control, applying a recommendation rule that interrelates the first
control and a second
control of the interactive form to retrieve from a local cache at the client
device at least one
recommended value for the second control, wherein the second control is
unfilled when the value
of the first control is received at the client device, and the at least one
recommended value
represents another portion of the travel-related search query. The method
further includes
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
3
displaying the at least one recommended value for the second control in the
interactive form at
the client device and the client device transmitting the travel-related search
query. The first
control and the second control, respectively, are one of a button, a slider, a
spinner, a list box, a
drop-down list and a combo box. The method may be embodied in a computer
program
product.
According to another embodiment of the present invention, a method is provided
that
receives at-a-server a plurality of values for a plurality of controls of an
interactive form, and
determines with the server a plurality of recommendation rules based upon the
values for
interrelated controls. Each value comprises a portion of a travel-related
search query entered
into one control of the interactive form by each of a plurality of users. Each
recommendation
rule logically connects two or more of the interrelated controls. Each of the
controls are one of a
button, a slider, a spinner, a list box, a drop-down list and a combo box. The
method may be
embodied in a computer program product.
According to another embodiment of the present invention, an apparatus is
provided
for use with a client device. The apparatus comprises a server including a
processor and
program code configured to be executed by the processor to interact with an
interactive form.
The program code is configured to cause the processor to receive a value for a
first control of the
interactive form, to apply a recommendation rule that interrelates the first
control and a second
control of the interactive form to determine at least one recommended value
for the second
control, and to communicate the at least one recommended value for the second
control from the
server to the client device. . The second control is unfilled when the value
for the first control is
received at the server the value for the first control and the at least one
recommended value for
the second control represent different portions of the travel-related search
query. The first control
and the second control, respectively, are one of a button, a slider, a
spinner, a list box, a drop-
down list and a combo box.
According to another embodiment of the present invention, an apparatus
comprises a
client device including at least one processor and a local cache. The
apparatus further comprises
program code configured to be executed by the processor to interact with an
interactive form.
The program code is configured to cause the processor to receive a value for a
first control of the
interactive form, to apply a recommendation rule that interrelates the first
control and a second
control of the interactive form to retrieve from the local cache at the client
device at least one
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
4
recommended value for the second control in response to receipt of the value
of the first control
input into the interactive form, to display the at least one recommended value
for the second
control in the interactive form at the client device and to transmit a travel-
related search query
comprising the value of the first control and the at least one recommended
value for the second
control.. The second control is unfilled when the value of the first control
is received at the
client device, and the value of the first control and the at least one
recommended value for the
second control represent different portions of the travel-related search
query. The first control
and the second control, respectively, are one of a button, a slider, a
spinner, a list box, a drop-
down list and a combo box.
According to another embodiment of the present invention, an apparatus
comprises a
server including processor and program code configured to be executed by the
processor to
interact with an interactive form. The program code is configured to cause the
processor to
receive a plurality of values for a plurality of controls of the interactive
form, and determine a
plurality of recommendation rules based upon the values for interrelated
controls. Each value
represents a portion of the travel-related search query entered into one of
the controls of the
interactive form by a plurality of users. Each recommendation rule logically
connects two or
more of the interrelated controls. The first control and the second control,
respectively, are one
of a button, a slider, a spinner, a list box, a drop-down list and a combo
box.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of
this
specification, illustrate various embodiments of the invention and, together
with a general
description of the invention given above and the detailed description of the
embodiments given
below, serve to explain the embodiments of the invention.
FIG. 1 is a block diagram of a computer reservation system that includes a
server and
a client device in communication with the server in accordance with
embodiments of the
invention.
FIG. 2 is a block diagram of the client device of FIG. 1.
FIG. 3 is a diagrammatic view of the interactive form residing on the client
device.
FIG. 4 is a block diagram of the server of FIG. 1.
FIG. 5 is a flow chart illustrating the recommendation process.
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
FIG. 6 is a flow chart illustrating a learning process at the server that
prepares
recommendation rules for use in the recommendation process.
DETAILED DESCRIPTION
5 With reference to FIG. 1, computerized reservation system (CRS) 10
includes a
server 12 and a client device 16 that is coupled in communication over a
communication network
14 with the server 12. The CRS 10 may be used to store and retrieve
information and conduct
on-line transactions related to goods and services, such as the online search,
booking, and
purchase of tickets for air travel. In the context of air travel, the CRS 10
is configured to respond
to travel search queries by identifying particular flights that satisfy a
given itinerary, and to make
or book reservations for those flights. The CRS may be a proprietary computer
system allowing
real-time access to airlines fares, schedules, and seating availability and
other data, and may be
accessed by travel vendors, such as travel agencies, online travel vendors,
and travel companies,
to make bookings. The CRS 10 may be embodied in a global distribution system
(GDS), which
is a type of CRS that books and sells air travel tickets for multiple
airlines, as well as other
related travel items such as hotels, rental cars, etc.
The server 12, which is remote from the client device 16, may generally
comprise one
or more interconnected computing devices/systems located locally and/or
remotely and
configured to perform one or more operations associated with the server 12.
Communication
network 14 generally comprises one or more interconnected communication
networks, including
for example, a local area network (LAN), a wide area network (WAN), a public
network (e.g.,
the Internet using an Internet Service Provider), an enterprise private
network, a cellular
network, and/or combinations thereof. The interface connecting the server 12
and client device
16 may employ one or more suitable communication protocols defining rules and
data formats
for exchanging information and communicating over the network 14, such as User
Datagram
Protocol/Internet Protocol (UDP/IP), and/or Transmission Control
Protocol/Internet Protocol
(TCP/IP).
During a given session, a user of the client device 16 may be in communication
over
the communications network 14 with the server 12 for the representative
purpose of planning an
itinerary for a trip. However, while a single client device 16 is depicted in
Fig. 1, it is
understood that multiple different users may communicate with the server for
the same purpose
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
6
using different client devices 16. The multiple different users constitute a
pool of users that
communicate with the server 12 for the purpose of making travel search queries
by entering
information into the fields or controls of the same interactive form 40 (FIG.
3).
In brief, values entered by a user into fields or controls of the interactive
form 40 at
the client device 16 are communicated over the network 14 to the server 12. A
recommendation
module 62 at the server 12 stores the received control values in a history
database 80 and may
retrieve the-stored values from the history database 80, as indicated by the
double headed arrow
13. The stored values may be associated with a particular user in a record of
the history database
80 so as to establish user preferences and a user history. The recommendation
module 62 at the
server 12 queries a recommendation rules database 64 to access a set of
recommendation rules
stored in the recommendation rules database 64 to logically generate
suggestions in the form of
recommendations for controls of the interactive form 40. The retrieved
recommendation rules
match the query and reflect interrelated controls in the interactive form 40
for which
recommendation rules have been established. The query of the recommendation
rules database
82 is represented by the double-headed arrow 15 in FIG. 1. The recommendations
represent
predicted control values of comparatively high probability and may serve to
relieve the user of
the interactive form 40 from being required to select values for one or more
controls of the
interactive form 40 necessary to generate, for example, a trip booking query.
Recommendations
are communicated from the server 12 to the client device 16 and used by the
client device 16 to
adapt the interactive form 40. The recommendation process may be synchronous
with the user
entry of control values and the continuous data flow from the client device
16. A monitoring
module 66 functions as described below in conjunction with the operation of
the
recommendation module 62 to monitor the received control values.
A learning module 64 queries the history database 80 to retrieve stored values
of
historical user entries for the controls of the interactive form 40, as
indicated by the arrow 17.
The learning module 64 uses an algorithm to compute recommendation rules for
interrelated
controls of the interactive form 40. The learning module 64 may access
predefined business
rules stored in a business rules database 84 as indicated by double-headed
arrow 19 and/or static
parameters stored in a parameters database 86 as indicated by double-headed
arrow 21. The
learning module 64 is configured to manipulate the content of the
recommendation rules
database 82 by inserting new recommendation rules and updating or deleting
existing
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
7
recommendation rules, as indicated by arrow 23. Each recommendation rule
computed by the
learning module 64 interrelates different controls that are logically capable
of being interrelated.
With reference to FIG. 2 in which like reference numerals refer to like
features in
FIG. 1, the client device 16 includes one or more processing units 20
configured to execute one
or more instructions to perform and/or cause components of the client device
16 to perform one
or more operations consistent with embodiments of the invention. The client
device 16 may be
any type of electronic device, such as a mobile telephone, a smartphone, a
tablet computer, a
personal digital assistant (PDA), a desktop computer, a laptop computer, a
notebook computer,
etc., typically used to interact with an interactive form 40 to perform a
travel-related search
query.
The client device 16 includes an input/output ("I/O") interface 22, a display
24, and
external devices 26. The I/O interface 22 of client device 16 may be
configured to receive data
from the display 24 and data from the external devices 26 that is communicated
to the processing
unit 20 and may be configured to output data from the processing unit 20 to
the display 24 and
external devices 26. The display may be, for example, a computer monitor or a
screen on a
mobile phone or a tablet. Alternatively, the display 24 may be a touch screen
that not only
functions to permit a user to receive and view output data, but also functions
to permit the user to
input data with, for example, an onscreen virtual keyboard. The external
devices 26 may
includejor example, additional user input devices such as a keyboard, a
keypad, a mouse, a
microphone, etc., and additional user output devices such as speakers, etc.
The client device 16
may also include a network adapter 28, such as a network interface card or a
transceiver, that
supplies the physical connection with the network 14 and that is configured to
transmit data to
the server 12 and receive data from the server 12 over the network 14. In one
embodiment, the
client device 16 may communicate with the network 14 under an agreement with a
mobile
service provider as known in the art.
A memory 30 of the client device 16 is configured to store a software module
or
application 32 and/or an operating system 34, where the client application 32
and operating
system 34 each generally comprise one or more instructions stored as program
code that may be
read from the memory 30 by each processing unit 20. The instructions, when
executed by the
processing unit 20, may cause each processing unit 20 to perform one or more
operations to
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
8
thereby perform the steps necessary to execute steps, elements, and/or blocks
embodying the
various embodiments of the invention.
The memory 30 may represent random access memory (RAM) comprising the main
storage of a computer, as well as any supplemental levels of memory, e.g.,
cache memories, non-
volatile or backup memories (e.g., programmable or flash memories), mass
storage memory,
read-only memories (ROM), etc. In addition, the memory 30 may be considered to
include
memory storage physically located elsewhere, e.g., cache memory in a processor
of any
computing system in communication with the client device 16, as well as any
storage device on
any computing system in communication with the client device 16 (e.g., a
remote storage
database, a memory device of a remote computing device, cloud storage, etc.).
The client application 32 in the memory 30 runs locally on the client device
16 and its
program code may comprise instructions that, when executed by each processing
unit 20,
facilitates the creation and operation of an interactive form 40 (FIG. 3). The
interactive form 40
provides an interface between a user of the client device 16 and the server 12
that is located at a
remote location from client device 16. Accordingly, a user may interact with
an interactive form
40 (FIG. 3) displayed on the display 24.
The client application 32 may display the interactive form 40 to the user on
display
24 at the client device 16. The interactive form 40 may be displayed in a
graphical user interface
in which the information and actions for form 40 are available to the user of
the client device 16
through graphical icons and visual indicators. For example, the interactive
form 40 may be
displayed as a web page on a browser 50 (FIG. 3), which may be constituted by
a software
application associated with the operating system 34 and that provides web
browsing
functionality. The browser 50 may comprise a mobile browser specifically
designed for use on a
mobile device, such as a mobile phone or a tablet. A markup language, such as
HyperText
Markup Language (HTML), creates the interactive form 40 for display in the
browser 50. For
example, the markup language can embed scripts from a scripting language that
affect the
behavior of the interactive form 40. Alternatively, the client application 32
may also comprise a
mobile application (i.e., a mobile app) designed to run on a smartphone, a
tablet computer, or
other mobile device and that is downloaded from an application distribution
platform, such as a
network-accessible location (e.g., a mobile application store or an accessible
database), a
computer-readable storage media, etc.).
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
9
The client device 16 may further comprise a local cache 38 that is accessible
to the
processing unit 20. The local cache 38 may be a section of memory 30
configured to locally
store copies of data received, for example, from the server 12.
With reference to FIG. 3, the interactive form 40 allows a user to enter data
at the
client device 16 and then to communicate the entered data over the network 14
to the server 12
for processing. The interactive form 40 may include a variety of different
user interface
elements and, in particular, user interface elements in the form of controls
42, 43, 44, 45, 46 that
facilitate user input of content, such as control values. Additional controls
(not shown) may
appear as interface elements of the interactive form 40. The data entered into
the interactive
form 40 may be related to travel, such as a travel search query for the
purpose of travel booking
as described in the representative embodiment. However, other types of travel-
related
applications, such as itinerary management, flight status, etc., that are also
heavily dependent on
interactive forms and interactive form flows may benefit from the embodiments
of the invention.
The controls 42, 43, 44, 45, 46 may include, a button, a slider, a spinner, a
list box, a
drop-down list, and a combo box. Each control may include one or more labels
or captions that
provide textual context to the subject matter that can be input as a value for
the control. The
controls 42, 43, 44, 45, 46 on the interactive form 40 function as an input
template for new data
comprising user-entered values, and can display data supplied to the
interactive form 40 from,
for example, control values supplied from the server 12.
A button is a control that can be clicked upon to perform an action.
Representative
buttons include, but are not limited, to a check box that can be clicked upon
to select or deselect
(i.e., toggle) an option, a set of radio button that can be clicked upon to
select an option from a
selection of options from which only one option can be selected at once, and a
split button that
combines the functionality of a button, typically invoking some default
action, with a drop-down
list prompting related, secondary actions.
A slider has an indicator that can be moved vertically or horizontally to
select a value
for an item or, if two indicators are present, comprises a double slider that
permits selection of a
range of values for an item. A spinner is a value input control with arrow-up
and arrow-down
buttons that permit a user to step through a range of values.
A list box allows the user to select one or more items from a list contained
within a
static, multiple line text box. A drop-down list is similar to a list box in
that a list of items is
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
displayed from which a user can select. Unlike a list box, a drop-down list is
not permanently
expanded to show the items of the list but is instead dynamic. When a drop-
down list is inactive,
a single item is displayed. When a drop-down list is activated, a list of
items is displayed from
which the user may select one of the items. After the user selects a new item,
the drop-down list
5 reverts to the inactive state and displays the selected value. A combo
box is a variation of a drop
down list that combines an editable text input field with a list box so that
the user can make one
or more entries absent from the list of items.
The form may also include one or more text boxes. A text box is associated
with an
editable text input field and allows the user to input of one or more lines or
strings of text as
10 values into the interactive form 40. A user can enter text using a
keyboard, navigate and select
portions of text using the keyboard, mouse, or touch screen, and edit
previously-entered text.
The controls 42, 43, 44, 45, 46 of the interactive form 40 may include travel-
specific
controls. One type of travel-specific control is an auto-complete-and-select
group for locations,
such as an origin for a travel search query or a destination for the travel
search query, that
facilitates selection of a specific location by name or International Air
Transport Association
(IATA) code. Other travel-specific controls may include, but are not limited
to, an infant
selector that is used to select a number of infants, a round trip toggle that
selects whether or not a
trip is a round trip, a date picker that provides a calendar control to allow
selection of a date, a
start and end date picker that is a calendar control that allows selection of
a date range, a time
slider that provides a 12-hour or 24-hour time selector, a time range selector
in the interactive
form 40 of a double slider, a special service request selector that permits a
user to enter special
preferences for a trip, and a service cabin selector (economy, business class,
etc.).
One or more choices for a particular one of the controls 42, 43, 44, 45, 46
may be
indicated and/or selected by the user using the display 24 and/or external
devices 26 (FIG. 2).
For selection, the user may select values for a control by depressing keys on
the keyboard or
click buttons on a mouse, positioning a cursor by using the keyboard or mouse,
touching the
screen of the display 54 with a fingertip or an electromechanical input
device, speaking to a
voice-recognition system, etc.
The interactive form 40 is controlled and enriched through a scripting
language, such
as JavaScript, to permit dynamic creation and modification of the interactive
form 40. In
particular, the scripting language functions to influenced the content and
visual behavior of the
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
11
controls 42, 43, 44, 45, 46. As examples, a check-box can be pre-selected,
selection options for
a drop-down list can be sorted by importance, a date range for a slider can be
preset, a text box
can be pre-filled with data, the auto-complete options of a text box can be
set, etc. The control
and enrichment of the interactive form 40 may be provided by a JavaScript
library of pre-written
JavaScript and a JavaScript interpreter including in the client application 32
(FIG. 2). The
JavaScript interpreter interprets JavaScript source code in the JavaScript
library and executes the
script accordingly. The scripting language builds the interactive form 40 and
the user interface
elements of the interactive form 40, accepts content input into the controls,
pre-validates the data
input into the controls and/or prepares the form data to send from the client
device 16 to the
server 12, and causes content received by the client device 16 from the server
12 to be output to
controls 42, 43, 44, 45, 46 that have yet to be filled or otherwise addressed
by user input and/or
displayed to the user on the interactive form 40.
Client application 32 may further include program code that enables data
exchange
between the client device 16 and the server 12. In one embodiment, the data
exchange may
occur in an asynchronous, non-blocking manner using AJAX, Extensible Messaging
and
Presence Protocol (XMPP), etc. and is initiated by the client device 16. The
client application 32
can send data to, and retrieve data from, the server 12 asynchronously and in
the background
preferably without interfering with the display and behavior of the
interactive form 40.
Alternatively, push technologies may be used in which requests for data
exchange are initiated
by the server 12.
With reference to FIG. 4 in which like reference numerals refer to like
features in
FIG. 1, the server 12 includes one or more processing units 58 for executing
one or more
instructions to perform and/or interact with client device 16 to perform one
or more operations
consistent with embodiments of the invention. The server 12 includes a memory
60 accessible
by the one or more processing units 58. The memory 60 of the server 12 is
configured to store
software applications or modules 62, 64, 66, 68 and/or an operating system 70,
where the
modules 62, 64, 66, 68 and operating system 70 each generally comprise one or
more
instructions stored as program code that may be read from the memory 60 by
each processing
unit 58. The instructions, when executed by the processing unit 58, may cause
each processing
unit 58 to perform one or more operations to thereby perform the steps
necessary to execute
steps, elements, and/or blocks embodying the various embodiments of the
invention.
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
12
The memory 60 may represent RAM comprising the main storage of a computer, as
well as any supplemental levels of memory, e.g., cache memories, non-volatile
or backup
memories (e.g., programmable or flash memories), mass storage memory, ROM,
etc. In
addition, the memory 60 may be considered to include memory storage physically
located
elsewhere, e.g., cache memory in a processing unit of any computing system in
communication
with the server 12, as well as any storage device on any computing system in
communication
with the server 12 (e.g., a remote storage database, a memory device of a
remote computing
device, cloud storage, etc.).
Server 12 further includes an input/output ("I/O") interface 72, a display 74,
and
external devices 76. The I/O interface 72 of server 12 may be configured to
receive data from
the display 74 and data from the external devices 76 that is communicated to
the processing unit
58 and may be configured to output data from the processing unit 58 to the
display 74 and
external devices 76. The display 74 and external devices 76 may function to
permit a user, such
as an administrator, to receive output data from server 12 and/or to supply
input data to the
server 12. The server 12 may also include a network adapter 78 that supplies
the physical
connection with the network 14 and that is configured to transmit data to the
client device 16
and/or receive data from the client device 16 over the network 14. The network
adapter 78 may
be a hardwired link such as an IEEE 802.3 (Ethernet) link, a wireless link
using a wireless
network protocol such as an 802.11 (Wi-Fi) link, or any other suitable link
for interfacing the
server 12 with the network 14.
The memory 60 also includes a history database 80, a recommendation rules
database
82, a business rules database 84, and a parameters database 86. Each of the
databases 80, 82, 84,
86 contains data and supporting data structures storing and organizing the
data. In particular,
each of the databases 80, 82, 84, 86 represents a structured collection of
data that may be
arranged with any database organization and/or structure, including but not
limited to a relational
database, a hierarchical database, a network database, and/or combinations
thereof. A database
management system in the form of a computer software application executing as
instructions on
the processing unit 58 is used to access the information or data stored in
records of the databases
80, 82, 84, 86 in response to a query. Each of the databases 80, 82, 84, 86
organizes and stores
the corresponding data in a data so that the data can be used efficiently. The
organization of the
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
13
data may support processes requiring the information (e.g., finding a
recommendation rule in the
recommendation rules database 82.
The recommendation module 62 at the server 12 directly interacts with the
client
device 16. The recommendation module 62 receives the values that have been
entered into the
controls 42, 43, 44, 45, 46 of the interactive form 40 or selected by the user
in the controls 42,
43, 44, 45, 46 of the interactive form 40. The recommendation module 62 stores
all user-
selected values received from the interactive form 40 in the history database
80. In parallel with
the storage process, the received values are also used to feed a probabilistic
reasoning process
based on partial user entry that invokes a set of recommendation rules stored
in the
recommendation rules database 82. In response to a partial travel search
query, the
recommendation module 62 queries the recommendation rules database 82 and
receives one or
more recommendation rules that are appropriate to the context of the query.
The query may be
constructed using a query language, such as Structured Query Language (SQL).
The recommendation module 62 applies the recommendation rules to determine
predicted values for unfilled controls in the interactive form 40 from a known
set of values for
filled form controls. For example, a plurality of known values for multiple
controls may lead to
a recommendation for one or more unfilled controls having a statistical
correlation and,
preferably, a recommendation for one or more values for each of several
controls that have a
statistical correlation in the form of probabilistic dependencies. Each
recommended value of a
recommendation may be communicated from the server 12 to the client device 16.
The client application 32 at the client device 16 may use a recommended value
received from the server 12 to pre-fill or pre-populate one of the controls
prior to any user entries
into the control, to order values to be suggested to the user in a control, to
make other
adaptations to the interactive form 40 (e.g., mask options in a control), etc.
The result is that,
based upon a known set of one or more filled controls in the interactive form
40, at least one
recommendation rule embodying a value or a likely values of one or more
unfilled controls in
the interactive form 40 is applied by the recommendation module 62 for the
function of
populating unfilled controls in the interactive form 40 and thereby
facilitates a simplified entry
of the travel search query by the user of the client device 16.
The recommendations made by the recommendation module 62 may also consider
personal historical data of the user at the client device 16. For example, the
identity of the user
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
14
may be known (i.e., a registered user) and the recommendation module 62 may
have access to
the user's personal history data regarding past recommendations. The user may
be a registered
user for whom preferences of values for controls are stored and thereby known
as personal
history data. User preferences for a control derived from the personal history
data may be
considered in conjunction with the control values derived from the
recommendation rules.
The recommendations made by the recommendation module 62 may also consider
information relating to the context of the client device 16. For example, the
client device 16 may
communicate device-dependent information, such as location, as data to the
server 12 for use in
making recommendations. The client device 16 may also communicate other types
of device-
independent information comprising data that can be found and/or computed on
the client device
16, such as time of day, day of the week, etc. These types of information may
also be considered
by the recommendation module 62 when making recommendations.
The learning module 64 is configured to input data from a plurality of data
sources
and to train a predictive algorithm used to generate recommendation rules as
predictions related
to the data. In particular, the learning module 64 generates recommendation
rules between
controls of the interactive form 40 that are interrelated (i.e., mutually
related). The predictive
algorithm is based upon an assumption that some or all of the controls of the
interactive form 40
are statistically correlated, perhaps as correlated pairs of controls or as
correlated groups of
controls, such that entry of values into one or more controls influences the
predicted values for
more or more other controls. One or more controls may be statistically
correlated with one or
more other controls to provide the interrelationships that are the basis of
the recommendation
rules and applied by the predictive algorithm to compute the recommendation
rules. For
example, multiple controls may be statistically correlated with multiple other
controls to provide
an interrelationship.
The learning module 64 supplies the recommendation rules to the recommendation
rules database 82, which serves as a repository to store the recommendation
rules. The execution
of learning module 64 is decoupled from the execution of the recommendation
module 62. For
example, the learning module 64 may asynchronously run in regular cycles
(e.g., once per hour)
and without triggering by user interactions. In particular, learning module 64
may determine
recommendation rules independent of any type of triggering by user
interactions at the client
device 16.
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
One data source feeding the learning module 64 is the history database 80,
which
contains historical collaborative data accumulated from users that is
accessible to both of the
modules 62, 64. The history database 80 may store data as raw data or
aggregated data. The
recommendation module 62 writes data representing the selections of all users
of the interactive
5 form 40 to the history database 80. The history database 80 may be
updated in real time as user
selections are received from the client device 16 and all data instances,
whether raw data or
_ aggregated data, are refreshed in an incremental manner.
The learning module 64 reads the collaborative historical data of form
selections from
the history database 80 for use in generating recommendation rules. The input
data from the
10 history database 80 represents instances of possible relations between
observed user selections,
and the recommendation module 62 captures characteristics of interest of the
unknown
underlying probability distribution of the data in the history database 80.
The history database 80 may also include personal historical data of form
selections
that is correlated with each particular user of the interactive form 40 at the
client device 16. The
15 recommendation module 62 may read this personal historical data from the
history database 80
for use in generating a recommendation in conjunction with the recommendation
derived from
the application of recommendation rules from the recommendation rules database
82.
If the collaborative historical data is stored in the history database 80 as
raw data, the
learning module 64 will have access to all collaborative historical data
without limitation so that
the predictive algorithm can detect changes in the patterns of user selection.
For example, a
parameter relating to a user selection that is currently not important or
discriminating may
become important or discriminating in the future and, therefore, the raw data
is needed so that
the learning module 64 can adapt to the change. To accommodate the large
number of records,
the raw data must be organized in an intelligent manner, such as avoiding data
repetitions and
storing counts rather than individual records whenever possible without losing
granularity.
If the collaborative historical data is aggregated and stored as aggregated
data in the
history database 80, the learning module 64 is able to process the data more
quickly than if in
raw form. Storing data in an aggregated format eliminates the need to
aggregate data each time
that the learning module 64 is run.
Other data sources may be accessed by the learning module 64 during the
process of
determining the recommendation rules. For example, one such data source may be
the business
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
16
rules database 84, which contains predefined business rules. For example, a
representative
business rule may be that a majority of leisure trips include a Saturday night
stay. Yet another
data source that may be accessed by the learning module 64 is the parameters
database 86, which
contains static parameters. For example, a representative static parameter is
an instruction to
ignore a certain value for a control of the interactive form 40.
The learning module 64 may use one or more predictive algorithms to compute
the
recommendation rules for the recommendation rules database 82 based upon
probabilistic
tendencies of travelers. Generally, the recommendation rules will predict
control values that
track values for the controls selected by the largest proportion of users. The
recommendation
rules may be computed using the collaborative historical data in the history
database 80.
Representative predictive algorithms may be based upon, for example,
collaborative filtering or a
neural network. After a certain training period, the output of the algorithm
is a predictor that
defines recommendation rules, which can be used by the recommendation module
62 to propose
values for controls based on existing user entries in the partially-filled
interactive form 40. The
historical collaborative data from the history database 80 may be provided as
an initial training
set to the algorithm.
Collaborative filtering provides a representative embodiment of unsupervised
learning and, generally, filters large amounts of information using algorithms
that process data
from multiple data sources. Collaborative filtering establishes correlations
between selected
values for different variables in the controls of the form (e.g., between
pairs of selected values)
and generates recommendations for the recommendation rules on at least this
basis.
Collaborative filtering derives the past behavior of travelers (i.e., form
selections) from the
collaborative history data in the history database 80 and uses that
collaborative history data to
predict the selections that a traveler might select if given the opportunity.
The predictions are
filtered using business logic from the business rules database 84 and
parameters database 86. In
this manner, the learning module 64 may use collaborative filtering to build
an item-by-item
matrix in the recommendation rules database 82 that specifies relationships
between values that
can potentially appear as use selections in the files of the controls of
interactive form 40.
A neural network provides a representative embodiment of supervised learning
and
generally is represented by a mathematical model or computational model used
to find patterns
in the collaborative history data in the history database 80. The neural
network is adaptive
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
17
system in that its structure can change based on the historical traveler data
supplied during a
learning phase. Based upon the collaborative history data received from the
history database 80,
the neural network may compute a model from a set of allowed models that
minimizes a given
cost criterion.
The learning module 64 also features one or more aggregation algorithms that
determine an optimal level of aggregation for values of form controls
associated with the
collaborative historical data in the history database 80. Aggregation may be
performed on any
set of values for one or more form controls and their associations, and are
usually specific to
travel, e.g., origin, destination, departure date, return date, airline, etc.
The aggregation
algorithm makes decisions of whether to aggregate control values based, as
examples, on the size
of the data set that is available and/or whether a particular control is or is
not discriminating.
One factor used in the decision to aggregate data for defining a
recommendation rule
is the size of the data set for the values of controls stored in the history
database 80. Contingent
upon the data set size, the aggregation algorithm may decide to aggregate
control values
according to increasingly coarse granularity in order to improve statistical
significance of the
recommendations. For example, values for an origin to a particular destination
may be
aggregated according to a major commercial airport as the origin, a
geographical region
including multiple major commercial airports confined to a region of a single
country as the
origin, or an even larger geographical region such as all major commercial
airports in a single
country as the origin. As a particular example, the historical data supplied
to the aggregation
algorithm for Nice-to-London trips may be too scarce to obtain a statistically
significant
prediction. In that eventuality, the aggregation algorithm may decide to
aggregate the data for all
France-to-London trips, which has coarser granularity and higher statistical
significance, as
representative of one or more recommendation rules for the Nice-to-London
trip.
The aggregations are determined for each set of control values in the history
database
80. In the particular example, the coarser aggregation is specific to Nice as
an origin in the
recommendation rules for Nice-to-London trips supplied to the recommendation
rules database
82. However, the fact that Nice-to-London recommendations are determined based
on France-
to-London data does not mean that the aggregation algorithm will decide to
base the
recommendations for any other airport in France as an origin for travel to
London upon an
aggregation of France-to-London data. For example, the history database 80 may
hold sufficient
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
18
data for Paris-to-London itineraries so that the aggregation algorithm may
decide that an
aggregation is not needed for that particular pair of origin and destinations.
The aggregation algorithm may decide that multiple aggregations are needed.
For
example, the data in history database 80 for a Nice-to-Salt Lake City
itinerary may be too small
to be considered by the aggregation algorithm to be statistically significant,
as well as the data in
history database 80 for travel from all major commercial airports in the
larger geographical unit,
the-nation France, to Salt Lake City. In this instance, the aggregation
algorithm may decide to
perform aggregation at a higher level, such as aggregating the data for travel
from all major
commercial airports in France to all major commercial airports in the western
United States for
use in determining the recommendation rules for travel from Nice to Salt Lake
City.
One factor used in the decision to aggregate data for defining a
recommendation rule
is that certain form controls may be considered to be discriminating. For
example, if the choice
of airline does not strongly depend on the duration of stay for a given pair
of origin and
destinations, then the duration of stay is not a discriminating form control
considered by the
aggregation algorithm for the determination of recommendations of the airline.
Accordingly, the
duration of stay may be disregarded and data records for various stay
durations may be
aggregated.
When computing the recommendation rules, the learning module 64 also utilizes
business rules contained in the records of the business rules database 84 and
static parameters in
the parameters database 86. The business rules and static parameters introduce
expert judgment
into the process defining the recommendation rules. However, the learning
module 64 is
designed in such a way that, even with no configuration, relevant
recommendation rules are
determined based on data from existing user traffic.
An example of a recommendation rule may be based upon a distribution of stay
durations among the pool of users for France-to-London trips having an
outbound leg on a
Friday. The recommendation rule may specify that the most probably stay
duration is two days,
the second most probable stay duration is three days, the third most probable
stay duration is
seven days, etc. If the partial travel search query received at the server 12
is for travel from
France to London departing on a Friday of a given week, then the
recommendation module 62
would invoke the recommendation rule to determine the most probable return
dates. The
recommendation module 62 would then cause the server 12 to communicate at
least one of the
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
19
return dates to the client device 16 for presentation to the user. For
example, a single return date
that is most probable may be communicated to the client device 16 for
populating a control in the
interactive form 40 that is a test box or multiple returns dates may
communicated to the client
device 16 for populating a control in the interactive form 40 that is a list
box to present the user
with a list that may be ranked according to probability.
The monitoring module 66 may be configured to compare recommendations supplied
to the client device-16 based upon the recommendation rules with the actual
selections of users.
The comparisons made by the monitoring module 66 may be used by, for example,
administration module 68.
The administration module 68 may be configured to provide an administrative
console that allows an administrator to observe the functioning of the system
and the
recommendation process. Based on this analysis, the administrator can modify
or otherwise alter
the business rules in the business rules database 84 and/or the static
parameters in the parameters
database 86 via the administration module 68 to influence the learning process
of the learning
module 64 and thereby the recommendation rules in the recommendation rules
database.
Alternatively, the administrator can define business rules for the business
rules database 84
and/or static parameters for the parameters database 86 via the administration
module 68. The
administration module 68 may also manually or automatically trigger the
running of the learning
module 64 with a given frequency. The administration module 68 may, for
example, detect
discrepancies, or track failures and weaknesses of the existing recommendation
process.
In an alternative embodiment of the invention, the data held in the local
cache 38
(FIG. 2) of client device 16 may include one or more recommendations received
from the server
12. The local cache 38 may temporarily hold the recommendations for use in
populating one or
more of the controls 42, 43, 44, 45, 46 in the interactive form 40 (FIG. 3)
based upon entry of
only a portion of a complete travel search query. For example, the local cache
38 may store a
number (e.g., three) of the most popular destinations as recommendations for
itineraries
originating at each of a number of origins as constrained by a physical size
of the storage space.
Having some or all of the recommendations at the client device 16 may speed
the
recommendation process. Selections made in the interactive form 40 at the
client device 16 may
still be communicated over the network 14 to the server 12, particularly upon
the actual input of
a less popular selection. The recommendation module 62 at the server 12 may
also cause
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
additional recommendations for the same control or for a different control to
be sent to the client
device 16 for presentation to the user and/or may store user selections in the
history database 80
as described herein.
In alternative embodiments of the invention, client application 32 at the
client device
5 16 may include the entire algorithm for the recommendation module 62 or,
at the least, a portion
of the algorithm of the recommendation module 62. The local recommendation can
rely on
values entered into thelorm controls by the user and held in the local cache
38 to provide
recommendations (e.g., the three most popular destinations based upon the user
history in the
local cache 38. The proportion of the algorithm executed at the client device
16 may be
10 contingent on the processing power, memory, etc. of the client device
16. Placing all or part of
the recommendation algorithm at the client device may speed the recommendation
process.
Despite the presence of all or part of the recommendation algorithm at the
client device 16, the
server 12 may still push recommended values to the client device 16. In this
manner, a limited
number of recommended control values may be made available at the client
device 16 from the
15 local cache 38 while awaiting the arrival of additional recommended
control values, possible for
the same control, from the server 12.
In another alternative embodiment of the invention, the local cache 38 (FIG.
2) of
client device 16 may be used to temporarily store values entered by the user
of the client device
16 as a local history. The client device 16 may transmit the contents of the
local history in the
20 local cache 38 over the network 14 to the server 12 so that the server
12 can update the history
database 80. For example, the client device 16 may dump the contents of the
local history to the
server 12 at a time of day when traffic over the network 14 is relatively
light. As another
example, if the client device 16 is a mobile device, the local history may be
communicated from
the client device 16 to the server 12 upon initial connection with the network
14.
With reference to FIG. 5, the receipt and processing of form data in
conjunction with
the provision of recommendations will be described. A user navigates to a
website (e.g., a travel
agency web site) in the browser or opens a mobile app at the client device 16,
connects with the
network 14, and initiates a session for communicating over the network 14 with
the server 12
using the interactive form 40 (block 100). In the representative embodiment,
the user initiates
entry of a travel search query using the interactive form 40. However, in
advance of any user
entry, one or more of the controls of the interactive form 40 may pre-filled
with a recommended
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
21
value. To initiate the pre-filling, one or more recommendations may be
retrieved from the local
cache 38 at the client device and used to provide the pre-filling.
The user may populate each of one or more of the controls in the interactive
form 40
at the client device 16, but not all of the controls of the interactive form
40, with a value to
partially enter a travel search query (block 102). The client application 32
detects the entry of
the partial travel search query into the interactive form 40 and causes the
processing unit 20 to
process the-values entered into the implicated controls. The client
application 32 running on the
processor 20 at the client device 16 causes the client device 16 to
communicate at least one
entered value or at least one entered behavior, and preferably all entered
values and behaviors, as
data over the network 14 to the server 12 (block 104). The client device 16
may also
communicate information relating to the context of the client device 16
(location, time of day,
etc.) to the server 12 for use in the recommendation process.
The recommendation module 62 receives the communicated data and stores the
values received from the client device in the history database 80 (block 106).
The
recommendation module 62 subjects the received values to an intelligent,
reasoning process that
invokes a set of recommendation rules to predict one or more recommendations
for one or more
of the unfilled controls in the interactive form 40 (block 108). Device-
independent information
(e.g., location) and device-dependent information (e.g., time of the day or
day of the week)
computed by or found at the client device 16 and communicated to the server 12
may also be
used by the recommendation module 62 in the computation of the
recommendations. Each
recommendation may comprise one or more recommended values for one or more of
the unfilled
controls in the interactive form 40 representing other portions of the travel-
related search than
the controls already filled by the user. The process flow may be repeated as
appropriate as
additional values are entered into the controls of the interactive form 40.
Preferably, the
population of multiple controls of the interactive form 40, after all values
are entered in block
104, is capable of influencing at least one other control of the interactive
form 40 with a
recommendation determined in block 108.
For example, after the session is initiated by the user at the client device
16 for the
interactive interchange of information with the server 12, the client
application 32 running on the
processor 20 at the client device 16 may retrieve recommendations for
populating one or both of
controls 42, 43 in the interactive form 40 with origin and destinations for a
trip booking. In one
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
22
embodiment, the processor 20 may retrieve the recommendations from the local
cache 38 and
present those recommendations in controls 42, 43. Alternatively, the client
device 16 may
communicate the session initiation to the server 12 and the recommendation
module 62 running
on the processor at the server 12 may cause recommendations for controls 42,
43 to be
determined using the recommendation rules in the recommendation rules database
82 and
communicated from the server 12 back to the client device 16. Regardless of
source, the client
_ application 32 may_cause controls 42, 43 in the interactive form 40 to be
populated with the
recommendations and other values appropriate for the context of control 42, 43
with the values
optionally sorted to present the recommended value(s) more highly ranked.
As another example, after the session is initiated by the user at the client
device 16 to
interactively interchange information with the server 12, the user may
populate the control 42 in
the interactive form 40 with a text string as an entry representing an origin
for a trip booking.
The application 32 running on the processor 20 at the client device 16 may
retrieve a
recommendation from the local cache for populating control 43 in the
interactive form 40 with
one or more destinations for a trip booking. Alternatively, the client device
16 may
communicate the origin to the server 12 and the recommendation module 62
running on the
processor at the server 12 may cause a recommendation for control 43 to be
determined using the
recommendation rules in the recommendation rules database 82 and communicated
from the
server 12 back to the client device 16. The recommendation received at the
client device 16
from the server 12 may be a text string with one recommended value for a
destination that is
most probable given the origin, or multiple recommended values for a
destination (i.e., multiple
recommended destinations) that are the most probable given the origin. Control
43 may be
populated with the recommendation and optionally other values appropriate for
the context of
control 43 with the values optionally sorted to present the recommended
value(s) more highly
ranked in the listing. The user can select the recommended value or one of the
recommended
values without manual entry into the control 43 and without scrolling through
a list of values.
As another example, after a session is initiated at the client device 16, the
user may
populate controls 42, 43 with text strings respectively representing an origin
and a destination,
and may populate control 44 with a departure date. The application 32 running
on the processor
20 at the client device 16 may populate control 45 in the interactive form 40
with a
recommendation for a return date. The processor 20 may retrieve the
recommendation from the
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
23
local cache 38 at the client device 16. Alternatively, the client device 16
may communicate the
values for controls 42, 43, 44 entered by the user to the server 12 and the
recommendation
module 62 running on the processor at the server 12 may cause a recommendation
for control 45
to be determined using the recommendation rules in the recommendation rules
database 82 and
communicated back to the client device 16. The date value of the
recommendation may
represent a most probable return date given the origin, the destination, and
the departure date
-based upon-historical-values of user entries used to build the recommendation
rules in the
recommendation rules database 82. The user can be relieved of the task of
selecting the return
date and may proceed directly to the next step of the booking process. Even if
the return date is
not selected, the process of modifying the return date in the control 45 may
be simplified if the
predicted return date is closer on the calendar to the actual return date
than, for example, the
current date.
Recommended values based upon the recommendation rules may optionally be
combined with or adjusted by recommended values from personal historical data
in the history
database 80 of the contemporaneous user that entered the partial travel search
query at the client
device 16. One approach for making the combination is a weighted average of
each
recommended value based upon all users of the interactive form 40 and the
personal
recommended value for the contemporaneous user of the client device 16.
One or more recommendations for each implicated control of the interactive
form 40
is communicated from the server 12 back to the client device 16 (block 110).
Upon receipt, the
client application 32 at the client device 16 adapts the interactive form 40
based upon each
recommendation (block 112). The client application 32 may populate a
particular implicated
control in the interactive form 40 with one or more recommended values
received from the
server 12 or may populate a particular implicated control in the interactive
form 40 with one or
more recommended values and other values that are not recommended. The client
application 32
may also change the state of a particular implicated control in the
interactive form 40 to reflect a
recommended value.
The user of the interactive form 40 at the client device 16 may adopt or
select a
recommended value appearing in each adapted control. Alternatively, the user
can enter a non-
recommended value for one of the adapted controls and, therefore, may select a
value not among
the recommendations. For example, the user may select one recommended value
(e.g., a
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
24
destination) from among multiple recommended values (e.g., destinations)
populating an adapted
control. The recommendation, even if not selected by the user, may also aid
the user of the client
device in making a selection for one or more controls. As an example, the
recommended value
may be a date differing from the current date that is placed in a date picker
and allows selection
of a date on a calendar. Even if the recommended value is not selected, the
user of the client
device 16 may select a date using the date selector that is closer in time to
the recommended date
than the current date, which may ease the selection process.
It is noted that the provision with recommended values for controls of the
interactive
form 40 as described hereinabove assist the user to complete the interactive
form 40 and are,
thus, performed in the course of filling the interactive form 40 prior to
completion of the
interactive form 40. The complete travel search query e.g. represented by the
values of all
controls 42, 43, 44, 45, 46 (in alternative embodiments, a complete travel
search query may
already be admissibly constituted by a subset of the controls 42, 43, 44, 45,
46) may be used to
perform a search to be conducted for trips satisfying the values entered into
the interactive form
40. To this end, the client device 16 transmits the complete travel search
query to a respective
travel server. The results may be communicated to the client device 16 and
displayed on the
client device 16 to the user for evaluation and potentially booking one of the
trips.
With reference to FIG. 6, the processing of form data stored in the history
database 80
to generate recommendation rules for the recommendation rules database will be
described. The
learning module 64 accesses the stored user data in the history database 80
that chronicles
selections made in the various controls of interactive form 40 by a pool of
all client device users
(block 150). The learning module 64 may query the business rules database to
receive business
rules that pertain to the recommendation process (block 152). The learning
module 64 may
query the parameters database to receive static parameters that pertain to the
recommendation
process (block 154). The one or more predictive algorithms of learning module
64 analyze the
historical user data in conjunction with the information from the business
rules database and the
parameters database to generate recommendation rules (block 156). The
recommendation
process may be based on the behavior of users when filling the controls of the
interactive form
40 and may be independent of human expert judgment. However, human expert
judgment may
be used to influence recommendations through business rules and static
parameters. The
historical user data may be aggregated, as discussed hereinabove, for defining
a recommendation
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
rule is the size of the data set for the values of controls stored in the
history database 80.
Contingent upon the data set size, the aggregation algorithm may decide to
aggregate control
values according to increasingly coarse granularity in order to improve
statistical significance of
the recommendations. The learning module 64 supplies these recommendation
rules to the
5 recommendation rules database 82 for storage (block 158). The routine
then ends (block 160).
As described hereinabove, the recommendation module 62 accesses the
recommendation rules to
the recommendation rules database 82 in order to propose values for the
controls at the
interactive form 40 during future sessions of a user at the client device 16
based on partial user
entries.
10 The routines and/or instructions that may be executed by the one or
more processing
units of the server 12 and client device 16 to implement embodiments of the
invention, whether
implemented as part of an operating system or a specific application,
component, program,
object, module, or sequence of operations executed by each processing unit,
will be referred to
herein as "program modules", "computer program code" or simply "modules" or
"program
15 code." Generally, program modules may include routines, programs,
objects, components, logic,
data structures, and so on that perform particular tasks or implement
particular abstract data
types. Computer program code for carrying out operations for aspects of the
present invention
may be written in any combination of one or more programming languages,
including an object
oriented programming language such as Java, Smalltalk, C++ or the like and
conventional
20 procedural programming languages, such as the "C" programming language
or similar
programming languages. Given the many ways in which computer code may be
organized into
routines, procedures, methods, modules, objects, and the like, as well as the
various manners in
which program functionality may be allocated among various software layers
that are resident
within a typical computer (e.g., operating systems, libraries, API's,
applications, applets, etc.), it
25 should be appreciated that the embodiments of the invention are not
limited to the specific
organization and allocation of program functionality described herein.
The flowcharts, block diagrams, and sequence diagrams herein illustrate the
architecture, functionality, and operation of possible implementations of
systems, methods, and
computer program products according to various embodiments of the present
invention. In this
regard, each block in a flowchart, block diagram, or sequence diagram may
represent a segment
or portion of program code, which comprises one or more executable
instructions for
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
26
implementing the specified logical function(s) and/or act(s). Program code may
be loaded onto a
computer, other programmable data processing apparatus, or other devices to
cause a series of
operational steps to be performed on the computer, other programmable
apparatus or other
devices to produce a computer implemented process such that the instructions
which execute on
the computer or other programmable apparatus provide processes for
implementing the
functions/acts specified in the blocks of the flowcharts, sequence diagrams,
and/or block
diagrams herein. In certain alternative implementations, the functions noted
in the blocks may
occur in a different order than shown and described. For example, a pair of
blocks described and
shown as consecutively executed may be instead executed concurrently, or the
two blocks may
sometimes be executed in the reverse order, depending upon the functionality
involved. Each
block and combinations of blocks can be implemented by special purpose
hardware-based
systems that perform the specified functions or acts, or combinations of
special purpose
hardware and computer instructions.
The program code embodied in any of the applications described herein is
capable of
being individually or collectively distributed as a program product in a
variety of different forms.
In particular, the program code may be distributed using a computer readable
media, which may
include computer readable storage media and communication media. Computer
readable storage
media, which is inherently non-transitory, may include volatile and non-
volatile, and removable
and non-removable tangible media implemented in any method or technology for
storage of
information, such as computer-readable instructions, data structures, program
modules, or other
data. Computer readable storage media may further include RAM, ROM, erasable
programmable read-only memory (EPROM), electrically erasable programmable read-
only
memory (EEPROM), flash memory or other solid state memory technology, portable
compact
disc read-only memory (CD-ROM), or other optical storage, magnetic cassettes,
magnetic tape,
magnetic disk storage or other magnetic storage devices, or any other medium
that can be used to
store the desired information and which can be read by a computer.
Communication media may
embody computer readable instructions, data structures or other program
modules. By way of
example, and not limitation, communication media may include wired media such
as a wired
network or direct-wired connection, and wireless media such as acoustic, RF,
infrared and other
wireless media. Combinations of any of the above may also be included within
the scope of
computer readable media.
CA 02893806 2015-06-04
WO 2014/095008
PCT/EP2013/003758
27
The terminology used herein is for the purpose of describing particular
embodiments
only and is not intended to be limiting of the embodiments of the invention.
As used herein, the
singular forms "a", "an" and "the" are intended to include the plural forms as
well, unless the
context clearly indicates otherwise. It will be further understood that the
terms "comprises"
and/or "comprising," when used in this specification, specify the presence of
stated features,
integers, steps, operations, elements, and/or components, but do not preclude
the presence or
_.. addition of-one or more other features, integers, steps, operations,
elements, components, and/or
groups thereof. Furthermore, to the extent that the terms "includes",
"having", "has", "with",
"comprised of', or variants thereof are used in either the detailed
description or the claims, such
terms are intended to be inclusive in a manner similar to the term
"comprising."
While the invention has been illustrated by a description of various
embodiments and
while these embodiments have been described in considerable detail, it is not
the intention of the
applicants to restrict or in any way limit the scope of the appended claims to
such detail.
Additional advantages and modifications will readily appear to those skilled
in the art. For
example, the embodiments of the invention may be used in conjunction with
other travel-related
applications aside from travel booking and travel search queries, such as
itinerary management,
flight status, etc., that are also heavily dependent on interactive forms and
interactive form flows.
The invention in its broader aspects is therefore not limited to the specific
details, representative
methods, and illustrative examples shown and described. Accordingly,
departures may be made
from such details without departing from the spirit or scope of applicants'
general inventive
concept.
