Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships

• US 8,756,187 B2
• Filed: 06/17/2013
• Issued: 06/17/2014
• Est. Priority Date: 09/28/2011
• Status: Expired due to Fees

• Current Assignee: Nara Logics, Inc.
• Original Assignee: Nara Logics, Inc.
• Inventors: Wilson, Nathan R., Hueske, Emily A., Copeman, Thomas C.
• Primary Examiner(s): Hill, Stanley K
• Application Number:
  US13/919,301
• Publication Number:
  US 20130275511A1
• Time in Patent Office: 365 Days
• US Class Current: 706/46
• CPC Class Codes: G06N 3/02 Neural networks
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.

Claims

1. A method comprising:

receiving, at at least one server, attribute data for a plurality of users, the data relating to a plurality of attributes of a user and to at least a first venue for which the user has an affinity;

receiving, at the least one server, venue data for a plurality of venues, the venue data relating to a plurality of attributes of the venues;

receiving, at the least one server, review data for the plurality of venues, the review data reflecting the affinity of a plurality of reviewers for the plurality of venues;

accessing, at the least one server, a data network comprising nodes corresponding at least to the plurality of venues and the plurality of reviewers and further comprising links between said nodes, each link reflecting a strength of an interrelationship between at least two nodes, wherein at least a plurality of the link strengths are a function of at least the review data and the venue data, are further a function of both content-based and collaborative interrelationships, and are based in part on connection creep from collaborative interrelationships such that nodes having an interrelationship with a link strength at or above as redetermined value have at least a portion of the link strength reassigned to other nodal interrelationships;

determining, at the least one server and based on the link strengths and at least one venue parameter, a plurality of recommended venues having the strongest links to a user;

generating, at the least one server, recommendation data comprising at least one recommended venue; and

serving to a client device the recommendation data for display on a screen of the client device.

2. The method of claim 1, wherein at least a plurality of the link strengths are further a function of content-collaborative interrelationships.

3. The method of claim 1, wherein at least a plurality of the links are directionally asymmetric.

4. The method of claim 1, wherein the data network is configured to be dynamically updated by localized arithmetic operations on affected links.

5. The method of claim 1, wherein the data network comprises a first data structure for collaborative links and a second data structure, discrete from the first structure, for content-based links.

6. The method of claim 1, wherein the review data is gathered from review web sites.

7. The method of claim 1, further comprising retrieving and parsing cached search engine pages including reviews of venues.

8. The method of claim 1, where the link strengths are based in part on connection growth from collaborative interrelationships.

9. The method of claim 1, where the link strengths are based in part on second order interrelationships between venues.

10. The method of claim 1, further comprising providing a user interface comprising an overview section vertically disposed above a venue comparison section which is vertically disposed above a reservations section.

11. The method of claim 1, wherein the reassigned portion of the link strength is equally distributed to the other nodal interrelationships.

12. The method of claim 1, wherein the portion of the link strength is reassigned to one or more others nodes having an interrelationship with the node from which the reassignment was made.

13. A method for providing venue recommendations on a client device, comprising:

transmitting, from the client device to at least one server device, attribute data for a user, the data relating to a plurality of attributes of a user and to at least a first venue for which the user has an affinity;

transmitting, from the client device to the at least one server device, a recommendation request including at least one venue attribute;

receiving, from the at least one server device, data identifying a plurality of recommended venues, each recommended venue being selected based on the strength of a nodal interrelationship between the venue and the user within a data network comprising nodes corresponding at least to a plurality of venues and a plurality of reviewers and further comprising links between said nodes, each link reflecting a strength of an interrelationship between at least two nodes, wherein at least a plurality of the link strengths are a function of venue data relating to a plurality of attributes of the venues and review data reflecting the affinity of a plurality of reviewers for the plurality of venues, and wherein at least a plurality of the link strengths are further a function of both content-based and collaborative interrelationships and are based in part on connection creep from collaborative interrelationships such that nodes having an interrelationship with a link strength at or above a predetermined value have at least a portion of the link strength reassigned to other nodal interrelationships; and

displaying, on a screen of the client device, data identifying the plurality of recommended venues.

14. The method of claim 13, wherein at least a plurality of the link strengths are further a function of content-collaborative interrelationships.

15. The method of claim 13, wherein at least a plurality of the links are directionally asymmetric.

16. The method of claim 13, wherein the data network is configured to be dynamically updated by localized arithmetic operations on affected links.

17. The method of claim 13, wherein the data network comprises a first data structure for collaborative links and a second data structure, discrete from the first structure, for content-based links.

18. The method of claim 13, wherein the review data is gathered from review web sites.

19. The method of claim 13, further comprising retrieving and parsing cached search engine pages including reviews of venues.

20. The method of claim 13, where the link strengths are based in part on connection growth from collaborative interrelationships.

21. The method of claim 13, where the link strengths are based in part on second order interrelationships between venues.

22. The method of claim 13, wherein each affinity is optionally negative.

23. The method of claim 13, further comprising displaying, on the client device, a user interface comprising an overview section vertically disposed above a venue comparison section which is vertically disposed above a reservations section.