FreshPatents.com Logo
stats FreshPatents Stats
n/a views for this patent on FreshPatents.com
Updated: July 25 2014
newTOP 200 Companies filing patents this week


    Free Services  

  • MONITOR KEYWORDS
  • Enter keywords & we'll notify you when a new patent matches your request (weekly update).

  • ORGANIZER
  • Save & organize patents so you can view them later.

  • RSS rss
  • Create custom RSS feeds. Track keywords without receiving email.

  • ARCHIVE
  • View the last few months of your Keyword emails.

  • COMPANY DIRECTORY
  • Patents sorted by company.

Follow us on Twitter
twitter icon@FreshPatents

System and method for obtaining preferences with a user interface

last patentdownload pdfdownload imgimage previewnext patent


20120324367 patent thumbnailZoom

System and method for obtaining preferences with a user interface


Techniques for obtaining user preferences. The techniques include receiving user context information associated with at least one user; identifying, based at least in part on the received user context information, a plurality of attributes of items in a plurality of items; obtaining, using at least one processor, at least one first-order user preference based at least in part on a first input provided by the at least one user, wherein the plurality of first-order user preferences comprises a preference for a first attribute in the plurality of attributes; and obtaining, using the at least one processor, at least one second-order user preference based at least in part on a second input provided by the at least one user, wherein the at least one second-order user preference comprises a preference among attributes in the plurality of attributes.
Related Terms: First-order

Browse recent Primal Fusion Inc. patents - Waterloo, CA
Inventors: Ihab Francis Ilyas, Mohamed A. Soliman
USPTO Applicaton #: #20120324367 - Class: 715747 (USPTO) - 12/20/12 - Class 715 
Data Processing: Presentation Processing Of Document, Operator Interface Processing, And Screen Saver Display Processing > Operator Interface (e.g., Graphical User Interface) >For Plural Users Or Sites (e.g., Network) >Interface Customization Or Adaption (e.g., Client Server) >End User Based (e.g., Preference Setting)

view organizer monitor keywords


The Patent Description & Claims data below is from USPTO Patent Application 20120324367, System and method for obtaining preferences with a user interface.

last patentpdficondownload pdfimage previewnext patent

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application Ser. No. 61/498,899, filed on Jun. 20, 2011, titled “Method and Apparatus for Preference Guided Data Exploration.” The present application also claims the benefit under 35 U.S.C. §365(c) and §120 and is a continuation-in-part of PCT international application PCT/CA2012/000009, filed Jan. 6, 2012, and titled “Systems and Methods for Analyzing and Synthesizing Complex Knowledge Representations.”

PCT international application PCT/CA2012/000009 is a continuation of U.S. patent application Ser. No. 13/345,637, filed on Jan. 6, 2012, and titled “Knowledge Representation Systems and Methods Incorporating Data Consumer Models and Preferences,” which claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application Ser. No. 61/498,899, filed on Jun. 20, 2011, titled “Method and Apparatus for Preference Guided Data Exploration.”

PCT international application PCT/CA2012/000009 is also a continuation of U.S. patent application Ser. No. 13/345,640, filed on Jan. 6, 2012, and titled “Systems and Methods for Applying Statistical Inference Techniques to Knowledge Representations,” which is a continuation in part of U.S. patent application Ser. No. 13/165,423, filed Jun. 21, 2011, titled “Systems and Methods for Analyzing and Synthesizing Complex Knowledge Representations.”

PCT international application PCT/CA2012/000009 is also a continuation of U.S. patent application Ser. No. 13/345,644, filed on Jan. 6, 2012, and titled “Knowledge Representation Systems and Methods Incorporating Inference Rules,” which is a continuation in part of U.S. patent application Ser. No. 13/165,423, filed Jun. 21, 2011, titled “Systems and Methods for Analyzing and Synthesizing Complex Knowledge Representations.”

Each of the above-identified applications is hereby incorporated by reference in its entirety.

BACKGROUND

Information retrieval systems are capable of accessing enormous volumes of information. As a result, locating information of interest to users presents challenges. One such challenge is identifying information that may be of interest to users so that information may be presented to them without overwhelming users with irrelevant information. Even in environments, such as online search, where the user provides an explicit indication (e.g., a search query) of what information the user may be interested in, such an indication may not be sufficient to accurately identify the content which is appropriate to present to the user from among all the content that may be available to be presented to the user.

Conventional approaches to identifying information of interest to a user often shift the burden of finding such information to the user. For example, conventional approaches to search may involve presenting all potentially relevant results to a user in response to the user\'s search query. Subsequently, the user has to manually explore and/or rank these results in order to find the information of greatest interest to him. When the number of potentially relevant results is large, which is often the case, the user may be overwhelmed and may fail to locate the information he is seeking.

One technique for addressing this problem is to integrate a user\'s preferences into the process of identifying information of interest to the user. By presenting information to the user in accordance with his preferences, the user may be helped to find the information he is seeking. However, conventional approaches to specifying user preferences severely limit the ways in which user preferences may be specified, thereby limiting the utility of such approaches.

Consider, for example, a data exploration model adopted by many search services and illustrated in FIG. 1. Query interface 12 is used to collect query predicates in the form of keywords and/or attribute values (e.g., “used Toyota” with price in the range [$2000-$5000]). Query results are then sorted (14) on the values of one or more attributes (e.g., order by Price then by Rating) in a major sort/minor sort fashion. The user then scans (16) through the sorted query answers to locate items of interest, refines query predicates, and repeats the exploration cycle (18). This “Query, Sort, then Scan” model limits the flexibility of preference specification and imposes rigid information retrieval schemes, as highlighted in the following example.

Example 1

Amy is searching online catalogs for a camera to buy. Amy is looking for a reasonably priced camera, whose color is preferably silver and less preferably black or gray, and whose reviews contain the keywords “High Quality.” Amy is a money saver, so her primary concern is satisfying her Price preferences, followed by her Color and Reviews preferences.

The data exploration model of FIG. 1 allows Amy to sort results in ascending price order. Amy then needs to scan through the results, which are sorted by price, comparing colors and inspecting reviews to find the camera that she wants. The path followed by Amy to explore search results is mainly dictated by her price preference, while other preferences are incorporated in the exploration task through Amy\'s effort, which can limit the possibility of finding items that closely match her requirements.

Conventional approaches to specifying user preferences suffer from a number of other drawbacks in addition to not simultaneously supporting preferences for multiple attributes (e.g., price, color, and reviews). For example, preference specifications may be inconsistent with one another. A typical example is having cycles (or “circularity”) in preferences among first-order preferences (preferences among attributes of items such as preferring one car to another car based on the price or on brand). For instance, a user may indicate that a Honda is preferred to a Toyota, a Toyota is preferred to a Nissan, and a Nissan is preferred to a Honda. Even when first-order preferences are consistent, preferences among first-order preferences, termed second-order preferences (e.g., brand preferences are more important than price preferences) may result in further inconsistencies among specified preferences. Conventional information retrieval systems are unable to rank search results when preference specifications may be inconsistent.

SUMMARY

In some embodiments, a computer-implemented method for calculating a ranking of at least one item in a plurality of items is disclosed. The method comprises receiving user preferences comprising a plurality of first-order user preferences indicative of a user\'s preferences for items in the plurality of items, and at least one second-order user preference indicative of the user\'s preferences among first-order user preferences in the plurality of first-order user preferences. The method further comprises calculating, with at least one processor, a ranking of the at least one item in the plurality of items based, at least in part on, at least one data structure encoding a preference graph that represents the received user preferences, and identifying and outputting at least a subset of the plurality of items to a user, in accordance with the ranking.

In some embodiments, a system is disclosed. The system comprises at least one memory configured to store a plurality of tuples, each tuple in the plurality of tuples corresponding to an item in a plurality of items, and at least one data structure encoding a preference graph to represent user preferences, wherein the user preferences comprise a plurality of first-order user preferences indicative of a user\'s preferences among items in the plurality of items, and at least one second-order user preference indicative of the user\'s preferences among first-order user preferences in the plurality of first-order user preferences. The system further comprises at least one processor coupled to the at least one memory, the at least one processor configured to calculate a ranking of at least one item in the plurality of items based, at least in part on, the at least one data structure encoding the preference graph that represents the user preferences, and identify and output at least a subset of the plurality of items to a user, in accordance with the ranking.

In some embodiments, at least one computer-readable storage medium article is disclosed. The at least one computer-readable storage medium article stores a plurality of processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method of calculating a ranking for at least one item in a plurality of items. The method comprises receiving user preferences comprising a plurality of first-order user preferences indicative of a user\'s preferences among items in the plurality of items, and at least one second-order user preference indicative of the user\'s preferences among first-order user preferences in the plurality of first-order user preferences. The method further comprises calculating a ranking of the at least one item in the plurality of items based, at least in part on, at least one data structure encoding a preference graph that represents the received user preferences, and identifying and outputting at least a subset of the plurality of items to a user, in accordance with the ranking.

In some embodiments, a computer-implemented method for constructing at least one data structure encoding a preference graph that represents user preferences is disclosed. The preference graph comprises a first node for a first item in a plurality of items, a second node for a second item in the plurality of items, and an edge between the first node and the second node. The method comprises receiving a plurality of first-order user preferences indicative of user preferences among values of attributes of items in the plurality of items, receiving at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, and computing, using at least one processor, a weight for the edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item.

In some embodiments, a system for constructing at least one data structure encoding a preference graph that represents user preferences is disclosed. The preference graph comprising a first node for a first item in a plurality of items, a second node for a second item in the plurality of items, and an edge between the first node and the second node. The system comprises at least on processor configured to receive a plurality of first-order user preferences indicative of user preferences among values of attributes of items in the plurality of items, receive at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, and compute a weight for the edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item.

In some embodiments, at least one computer-readable storage medium article is disclosed. The at least one computer-readable storage medium article stores a plurality of processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for constructing at least one data structure encoding a preference graph that represents user preferences. The preference graph comprises a first node for a first item in a plurality of items, a second node for a second item in the plurality of items, and an edge between the first node and the second node. The method comprises receiving a plurality of first-order user preferences indicative of user preferences among values of attributes of items in the plurality of items, receiving at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, and computing a weight for the edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item.

In some embodiments, a computer-implemented method for obtaining user preferences is disclosed. The method comprises receiving user context information associated with at least one user; identifying, based at least in part on the received user context information, a plurality of attributes of items in a plurality of item; obtaining, using at least one processor, at least one first-order user preference based at least in part on a first input provided by the at least one user, wherein the plurality of first-order user preferences comprises a preference for a first attribute in the plurality of attributes; and obtaining, using the at least one processor, at least one second-order user preference based at least in part on a second input provided by the at least one user, wherein the at least one second-order user preference comprises a preference among attributes in the plurality of attributes.

In some embodiments, a system for obtaining user preferences is disclosed. The system comprises at least one processor configured to receive user context information associated with at least one user; identify, based at least in part on the received user context information, a plurality of attributes of items in a plurality of items; obtain, at least one first-order user preference based at least in part on a first input provided by the at least one user, wherein the plurality of first-order user preferences comprises a preference for a first attribute in the plurality of attributes; and obtain at least one second-order user preference based at least in part on a second input provided by the at least one user, wherein the at least one second-order user preference comprises a preference among attributes in the plurality of attributes.

In some embodiments, at least one computer-readable storage medium article is disclosed. The at least one computer-readable storage medium article stores a plurality of processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for obtaining user preferences. The method comprises receiving user context information associated with at least one user; identifying, based at least in part on the received user context information, a plurality of attributes of items in a plurality of items; obtaining, using at least one processor, at least one first-order user preference based at least in part on a first input provided by the at least one user, wherein the plurality of first-order user preferences comprises a preference for a first attribute in the plurality of attributes; and obtaining, using the at least one processor, at least one second-order user preference based at least in part on a second input provided by the at least one user, wherein the at least one second-order user preference comprises a preference among attributes in the plurality of attributes.

In some embodiments, a computer-implemented method for specifying user preferences in a semantic network encoded in at least one data structure is disclosed. The method comprises receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user\'s preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user\'s preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

In some embodiments, a system for specifying user preferences in a semantic network encoded in at least one data structure is disclosed. The system comprises at least one processor configured to receive a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user\'s preferences among children of attributes of the at least one concept in the semantic network; receive at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user\'s preferences among attributes of the at least one concept; and perform at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

In some embodiments, at least one computer-readable storage medium article is disclosed. The at least one computer-readable storage medium article stores a plurality of processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for specifying user preferences in a semantic network encoded in at least one data structure. The method comprises receiving a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user\'s preferences among children of attributes of the at least one concept in the semantic network; receiving at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user\'s preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

The foregoing is a non-limiting summary of the invention, which is defined by the attached claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component that is illustrated in various figures is represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. In the drawings:

FIG. 1 is a diagram of a “query, sort, then scan” data exploration model, in accordance with prior art.

FIG. 2A is a diagram illustrating a relation, in accordance with some embodiments of the present invention.

FIG. 2B is a diagram illustrating a semantic network associated with a portion of the relation illustrated in FIG. 2A.

FIG. 3 is a flowchart of an illustrative preference modeling process, in accordance with some embodiments of the present invention.

FIG. 4 is a diagram illustrating scopes obtained from a relation, in accordance with some embodiments of the present invention.

FIG. 5 is a diagram illustrating scope comparators, in accordance with some embodiments of the present invention.

FIG. 6 is a diagram illustrating conjoint preferences, in accordance with some embodiments of the present invention.

FIG. 7 is a diagram of an illustrative mapping of a partial order to linear extensions, in accordance with some embodiments of the present invention.

FIG. 8 is a diagram of an illustrative preference graph, in accordance with some embodiments of the present invention.

FIG. 9 is a diagram of an illustrative computation of edge weights for different types of second-order preferences, in accordance with some embodiments of the present invention.

FIG. 10 is a diagram of an illustrative page-rank based matrix for prioritized comparators, in accordance with some embodiments of the present invention.

FIG. 11 is a diagram of an illustrative weighted preference graph and tournaments derived from it, in accordance with some embodiments of the present invention.

FIG. 12 is a flowchart for an illustrative process for interactively specifying user preferences, in accordance with some embodiments of the present invention.

FIG. 13 is a flowchart for an illustrative process for computing a ranking for one or more items based on user preferences, in accordance with some embodiments of the present invention.



Download full PDF for full patent description/claims.

Advertise on FreshPatents.com - Rates & Info


You can also Monitor Keywords and Search for tracking patents relating to this System and method for obtaining preferences with a user interface patent application.
###
monitor keywords



Keyword Monitor How KEYWORD MONITOR works... a FREE service from FreshPatents
1. Sign up (takes 30 seconds). 2. Fill in the keywords to be monitored.
3. Each week you receive an email with patent applications related to your keywords.  
Start now! - Receive info on patent apps like System and method for obtaining preferences with a user interface or other areas of interest.
###


Previous Patent Application:
System and a method for remotely using electrical devices
Next Patent Application:
Object transfer method using gesture-based computing device
Industry Class:
Data processing: presentation processing of document
Thank you for viewing the System and method for obtaining preferences with a user interface patent info.
- - - Apple patents, Boeing patents, Google patents, IBM patents, Jabil patents, Coca Cola patents, Motorola patents

Results in 0.74274 seconds


Other interesting Freshpatents.com categories:
Qualcomm , Schering-Plough , Schlumberger , Texas Instruments ,

###

All patent applications have been filed with the United States Patent Office (USPTO) and are published as made available for research, educational and public information purposes. FreshPatents is not affiliated with the USPTO, assignee companies, inventors, law firms or other assignees. Patent applications, documents and images may contain trademarks of the respective companies/authors. FreshPatents is not affiliated with the authors/assignees, and is not responsible for the accuracy, validity or otherwise contents of these public document patent application filings. When possible a complete PDF is provided, however, in some cases the presented document/images is an abstract or sampling of the full patent application. FreshPatents.com Terms/Support
-g2-0.1513
     SHARE
  
           

FreshNews promo


stats Patent Info
Application #
US 20120324367 A1
Publish Date
12/20/2012
Document #
13527900
File Date
06/20/2012
USPTO Class
715747
Other USPTO Classes
International Class
06F3/01
Drawings
18


First-order


Follow us on Twitter
twitter icon@FreshPatents