METHOD AND SYSTEM OF SCORING DOCUMENTS BASED ON ATTRIBUTES OBTAINED FROM A DIGITAL DOCUMENT BY EYE-TRACKING DATA ANALYSIS

• US 20130054622A1
• Filed: 09/15/2011
• Published: 02/28/2013
• Est. Priority Date: 08/29/2011
• Status: Active Grant

• Current Assignee: Buckyball Mobile, Inc.
• Original Assignee: Amit V. Karmarkar
• Inventors: Karmarkar, Sharada, Peters, Richard R., Karmarkar, Amit V.
• Granted Patent: US 8,719,278 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/436 using biological or physiological data of a human being, e.g. blood pressure, facial expression, gestures
• CPC Class Codes: G06F 16/903 Querying for retrieval from the web G06F16/953
• CPC Class Codes: G06F 16/9035 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

In one exemplary embodiment, a set of attributes derived from an element of a first digital document is obtained. The element is identified from eye-tracking data of a user viewing the digital document. A search query of a database comprising at least one query term is received. A set of documents in the database is identified according to the search query. An attribute score is determined for each document. The set of documents are sorted according to the attribute score. Optionally, a commonality between the query term and at least one member of the set of attributes may be determined. The search query may be generated by the user. The database may be a hypermedia database.

Claims

1. A computer-implemented method for scoring documents comprising:

obtaining a set of attributes derived from an element of a first digital document, wherein the element is identified from eye-tracking data of a user viewing the digital document;

receiving a search query of a database comprising at least one query term;

identifying a set of documents in the database according to the search query;

determining an attribute score for each document; and

sorting the set of documents according to the attribute score.

2. The computer-implemented method of claim 1, further comprising:

determining a commonality between the query term and at least one member of the set of attributes.

3. The computer-implement method of claim 2, wherein determining the attribute score for each document comprises:

determining a number of matches or a probability weight of a match between the set of attributes and each document.

4. The computer-implement method of claim 2, wherein determining the attribute score for each document comprises:

determining a number of matches between the set of attributes and at least one theme of each document.

5. The computer-implement method of claim 2, wherein the digital document comprises a web page.

6. The computer-implemented method of claim 5, wherein the element of the digital document comprises a text term.

7. The computer-implemented method of claim 5, wherein the element of the digital document comprises an image.

8. The computer-implemented method of claim 6, wherein attribute of the image comprises at least one of a color of the image or an object represented in the image.

9. The computer-implemented method of claim 2 further comprising:

obtaining a plurality of attributes from a plurality of digital documents over a specified period.

10. The computer-implemented method of claim of 9 further comprising:

scoring each attribute of the plurality of attributes based on a relevancy of each attribute to the user.

11. The computer-implemented method of claim of 10, wherein scoring each attribute of the plurality of attributes based on a relevancy of each attribute to the user further comprises:

determining a genre of each attribute of the plurality of attributes; and

scoring each genre based on a number of member attributes.

12. The computer-implemented method of claim of 10, wherein determining the attribute score for each document comprises:

determining a genre that is relevant to the search query; and

determining a number of matches between the attributes the relevant genre and the components of each document.

13. The computer-implemented method of claim of 1, wherein the search query is generated by the user.

14. The computer-implemented method of claim of 1, wherein the database is a hypermedia database.

15. A non-transitory computer-readable storage medium comprising computer-executable instructions for scoring a set of documents, the computer-executable instructions comprising instructions for:

obtaining at least one attribute derived from an element of a digital document, wherein the element is identified from eye-tracking data of a user viewing the digital document;

receiving a search query of a database comprising at least one query term;

identifying a set of documents in the database according to the search query;

determining an attribute score for each document; and

ranking the set of documents according to the attribute score.

16. The non-transitory computer-readable storage medium of claim 15, wherein the digital document comprises at least one of a web page, an augmented reality view, an image display of a digital camera or a multimedia messaging system message.

17. The non-transitory computer-readable storage medium of claim 15, wherein the attribute score of a document comprises a value determined by a comparison between a term vector representation of the document and the attribute.

18. The non-transitory computer-readable storage medium of claim 15 further comprising:

generating a database of attributes associated with a user viewing a plurality of digital documents over a specified period; and

ranking the database of attributes based on an attribute frequency value in the database.

19. The non-transitory computer-readable storage medium of claim 18, wherein the at least one attribute derived from the element of a digital document comprises at least a highest-ranked attribute.

20. A computer system for scoring a set of documents identified by a search query result, the system comprising:

memory configured to store the score of each document identified by a search query result; and

one or more processors configured to;

receive an attribute associated with an element of a visual interface displayed by user device, wherein the element is identified by eye-tracking data of the user viewing the element;

receive a search query of a database comprising at least one query term;

identify a set of documents in the database according to the search query;

determine an attribute score for each document; and

rank the set of documents according to the attribute score.

21. A device for processing eye-tracking data and displaying content, comprising:

a display screen;

an eye-tracking system comprising a camera; and

a processor configured to;

obtain eye-tracking data of a user'"'"'s ocular indices associated with a visual component, wherein the visual component is displayed on the display screen and wherein the eye-tracking data is obtained using at least the eye-tracking system,

transmit the obtained data to a server,

obtain a search query from the user;

transmit the obtained data to a search engine server;

receive a sorted search query response, wherein the search query response is sorted based on an attribute score, and wherein the attribute score is based on an attribute of the visual component, wherein visual component is determined based on the association of the eye-tracking data and the visual component, and

display the sorted search query results on the display screen.