METHOD AND APPARATUS FOR CATEGORY BASED NAVIGATION

• US 20130024456A1
• Filed: 07/19/2012
• Published: 01/24/2013
• Est. Priority Date: 07/20/2011
• Status: Active Grant

• Current Assignee: OpenTable, Inc. (Booking Holdings, Inc., fka Priceline Group Inc.)
• Original Assignee: NESS Computing Incorporated (Booking Holdings, Inc., fka Priceline Group Inc.)
• Inventors: Chatterji, Sourav, Schiff, Jeremy Ryan, Reese, Corey Layne, Twohey, Paul Kenneth, Goodson, Scott Paul
• Granted Patent: US 9,189,551 B2
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: G06F 16/33 Querying
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing

Abstract

Embodiments of the invention relate to a category based navigation system obtaining user data related to a plurality of users relevant to the primary user. The method further comprises obtaining entity data associated with an entity in a plurality of entities. The category based navigation system then determines one or more entities relevant to the primary user, and determines an initial order of relevance of a set of relevant entities. The method further comprises categorizing and displaying the set of relevant entities with an initial categorization on a user device to the primary user. The category based navigation system may then obtain, via the user device, user feedback, adjust the initial categorization and initial order of relevance based on the user feedback; and display the adjusted categorization and adjusted order of relevance of the set of relevant entities to the primary user on the user device.

Claims

1. A computer-implemented method for category based navigation for a primary user, the method comprising:

determining a set of relevant users, the relevant users being users deemed, by a computer evaluation process, to be relevant to the primary user, wherein the set of relevant users is a subset of data representing a plurality of users;

obtaining, at a server computer, user data related to the set of relevant users;

storing the user data at the server computer in a user database, wherein the user data base includes user data of other users of the plurality of users;

obtaining entity data from one or more data sources, wherein the entity data is associated with an entity in a plurality of entities, wherein the entity is associated with the target user;

storing the entity data at the server computer, wherein the entity data associated with the plurality of entities is stored in an entity database;

determining, at the server computer, a set of relevant entities comprising one or more entities relevant to the primary user based on the entity data and user data;

categorizing the set of relevant entities with an initial categorization;

displaying, on a user device, at least an indication of the initial categorization to the primary user;

obtaining, via the user device, user feedback related to the initial categorization;

adjusting the initial categorization based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

displaying the adjusted categorization and the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the categorization of entities in the set of relevant entities via the user device.

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

obtaining, at the server computer, location data associated with the target user, wherein the location data is associated with the categorization of an entity in a plurality of entities;

storing the location data at the server computer, wherein location data associated with the plurality of entities is stored in the entity database; and

adjusting the initial categorization and initial order of relevance based on the location data in the entity database.

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

obtaining, at the server computer, personal data from the plurality of data sources, wherein the personal data is associated with the primary user in the plurality of users;

storing the personal data at the server computer, wherein personal data associated with the plurality of users is stored in the user database;

merging, by the server computer, the personal data from the plurality of data sources;

mapping, by the server computer, the personal data from the plurality of data sources to the primary user;

updating the user database with the personal data and user data associated with the primary user;

determining, at the server computer, whether an entity is associated with the personal data from the primary user;

determining, at the server computer, whether the entity associated with the personal data corresponds with an entity associated with location data in the entity database;

mapping the entity associated with the personal data from the primary user to the corresponding entity associated with the location data;

determining, at the server computer, inferred location data based on the mapping;

updating the entity database to include the inferred location data associated with the corresponding entity; and

adjusting the initial categorization and initial order of relevance based on the personal data in the updated user database and the updated entity database.

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

determining an initial order of relevance of the set of relevant entities;

displaying, on a user device, at least an indication of the initial order of relevance to the primary user;

obtaining, via the user device, user feedback related to the initial order of relevance;

adjusting the initial order of relevance based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

displaying the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the relevance of entities in the set of relevant entities via the user device.

5. The computer-implemented method of claim 1, wherein determining the initial order of relevance or adjusted order of relevance is based on criteria.

6. The computer-implemented method of claim 5, wherein the criteria includes a number of responses initiated by the primary user to a specific category or relevant entity.

7. The computer-implemented method of claim 5, wherein the criteria includes one or more categories or entities that the primary user recently responded to.

8. The computer-implemented method of claim 5, wherein the criteria includes a current location of the primary user.

9. The computer-implemented method of claim 5, wherein the criteria includes a frequency in which the primary user interacts with a relevant entity.

10. The computer-implemented method of claim 1, wherein the initial order of relevance is random.

11. The computer-implemented method of claim 1, wherein a response via the user device includes finger gestures, clicking, shaking the user device, a coordinate motion between two user devices, blowing on the user device, spinning the user device, making a sound, or speaking a voice command.

12. The computer-implemented method of claim 1, wherein the displaying further comprises:

determining a set of media objects associated with the set of relevant entities; and

displaying the set of media objects with the set of relevant entities.

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

determining a navigation manner of the primary user;

storing the navigation manner in the user database; and

adjusting the initial categorization and initial order of relevance based on the navigation manner in the updated user database.

14. The computer-implemented method of claim 5, further comprising:

merging, by the server computer, the entity data from the plurality of data sources;

mapping, by the server computer, the entity data from the plurality of data sources to a corresponding entity;

differentiating, by the server computer, the entity data from the plurality of data sources associated with the corresponding entity;

determining, by the server computer, a relevance associated with the entity data and data source, wherein the relevance is determined by a computer process to cross-reference the entity data and data source;

assigning, by the server computer, a weight to the entity data and the data source associated with the entity data based on the relevance;

storing the weight to the entity data in the entity database; and

adjusting the initial categorization and initial order of relevance based on the weight in the updated entity database.

15. A computer-implemented method comprising:

categorizing a set of entities relevant to a primary user with an initial categorization, wherein the initial categorization is based on stored historical data related to the primary user;

displaying, on a user device, at least an indication of the initial categorization to the primary user;

obtaining, via the user device, user feedback related to the initial categorization;

adjusting the initial categorization based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

displaying the adjusted categorization and the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the categorization of entities in the set of relevant entities via the user device.

16. A server computer comprising a processor and a non-transitory computer-readable medium, the non-transitory computer-readable medium comprising code executable by the processor to implement a method for category based navigation for a primary user, the method comprising:

determining a set of relevant users, the relevant users being users deemed, by a computer evaluation process, to be relevant to the primary user, wherein the set of relevant users is a subset of data representing a plurality of users;

obtaining, at a server computer, user data related to the set of relevant users;

storing the user data at the server computer in a user database, wherein the user data base includes user data of other users of the plurality of users;

obtaining entity data from one or more data sources, wherein the entity data is associated with an entity in a plurality of entities, wherein the entity is associated with the target user;

storing the entity data at the server computer, wherein the entity data associated with the plurality of entities is stored in an entity database;

determining, at the server computer, a set of relevant entities comprising one or more entities relevant to the primary user based on the entity data and user data;

categorizing the set of relevant entities with an initial categorization;

communicating to the primary user, on a user device, at least an indication of the initial categorization to the primary user;

obtaining, via the user device, user feedback related to the initial categorization;

adjusting the initial categorization based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

communicating to the primary user, via the user device, the adjusted categorization and the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the categorization of entities in the set of relevant entities via the user device.

17. The server computer of claim 16, the method further comprising:

obtaining, at the server computer, location data associated with the target user, wherein the location data is associated with the categorization of an entity in a plurality of entities;

storing the location data at the server computer, wherein location data associated with the plurality of entities is stored in the entity database; and

adjusting the initial categorization and initial order of relevance based on the location data in the entity database.

18. The server computer of claim 17, the method further comprising:

obtaining, at the server computer, personal data from the plurality of data sources, wherein the personal data is associated with the primary user in the plurality of users;

storing the personal data at the server computer, wherein personal data associated with the plurality of users is stored in the user database;

merging, by the server computer, the personal data from the plurality of data sources;

mapping, by the server computer, the personal data from the plurality of data sources to the primary user;

updating the user database with the personal data and user data associated with the primary user;

determining, at the server computer, whether an entity is associated with the personal data from the primary user;

determining, at the server computer, whether the entity associated with the personal data corresponds with an entity associated with location data in the entity database;

mapping the entity associated with the personal data from the primary user to the corresponding entity associated with the location data;

determining, at the server computer, inferred location data based on the mapping;

updating the entity database to include the inferred location data associated with the corresponding entity; and

adjusting the initial categorization and initial order of relevance based on the personal data in the updated user database and the updated entity database.

19. The server computer of claim 16, the method further comprising:

determining an initial order of relevance of the set of relevant entities;

communicating to the primary user, on a user device, at least an indication of the initial order of relevance to the primary user;

obtaining, via the user device, user feedback related to the initial order of relevance;

adjusting the initial order of relevance based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

communicating, via the user device, the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the relevance of entities in the set of relevant entities via the user device.

20. The server computer of claim 16, wherein determining the initial order of relevance or adjusted order of relevance is based on criteria.

21. The server computer of claim 20, wherein the criteria includes a number of responses initiated by the primary user to a specific category or relevant entity.

22. The server computer of claim 20, wherein the criteria includes one or more categories or entities that the primary user recently responded to.

23. The server computer of claim 20, wherein the criteria includes a current location of the primary user.

24. The server computer of claim 20, wherein the criteria includes a frequency in which the primary user interacts with a relevant entity.

25. The server computer of claim 16, wherein the initial order of relevance is random.

26. The server computer of claim 16, wherein the response via the user device includes finger gestures, clicking, shaking the user device, a coordinate motion between two user devices, blowing on the user device, spinning the user device, making a sound, or speaking a voice command.

27. The server computer of claim 16, wherein the communicating further comprises:

determining a set of media objects associated with the set of relevant entities; and

displaying the set of media objects with the set of relevant entities.

28. The server computer of claim 16, the method further comprising:

determining a navigation manner of the primary user;

storing the navigation manner in the user database; and

adjusting the initial categorization and initial order of relevance based on the navigation manner in the updated user database.

29. The server computer of claim 20, the method further comprising:

merging, by the server computer, the entity data from the plurality of data sources;

mapping, by the server computer, the entity data from the plurality of data sources to a corresponding entity;

differentiating, by the server computer, the entity data from the plurality of data sources associated with the corresponding entity;

determining, by the server computer, a relevance associated with the entity data and data source, wherein the relevance is determined by a computer process to cross-reference the entity data and data source;

assigning, by the server computer, a weight to the entity data and the data source associated with the entity data based on the relevance;

storing the weight to the entity data in the entity database; and

adjusting the initial categorization and initial order of relevance based on the weight in the updated entity database.

30. A server computer comprising a process and a non-transitory computer-readable medium, the non-transitory computer-readable medium comprising code executable by the processor to implement a method comprising:

categorizing a set of entities relevant to a primary user with an initial categorization, wherein the initial categorization is based on stored historical data related to the primary user;

displaying, on a user device, at least an indication of the initial categorization to the primary user;

obtaining, via the user device, user feedback related to the initial categorization;

adjusting the initial categorization based on the user feedback to form an adjusted categorization and an adjusted order of relevance;

displaying the adjusted categorization and the adjusted order of relevance to the primary user; and

obtaining, from the primary user, a response to the categorization of entities in the set of relevant entities via the user device.