SYSTEMS AND METHODS FOR PROVIDING RECOMMENDATIONS BASED ON COLLABORATIVE AND/OR CONTENT-BASED NODAL INTERRELATIONSHIPS
First Claim
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;
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.
0 Assignments
0 Petitions
Accused Products
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.
-
Citations
21 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; 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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
-
11. 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; and displaying, on a screen of the client device, data identifying the plurality of recommended venues. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
-
Specification