Systems and methods for constructing and applying synaptic networks

Abstract

In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on 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.

What is claimed is: 
     
         1 . A method comprising:
 receiving 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 venue data for a plurality of venues, the venue data relating to a plurality of attributes of the venues;   receiving review data for the plurality of venues, the review data reflecting the affinity of a plurality of reviewers for the plurality of venues;   accessing 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 and wherein at least a plurality of the link strengths are further a function of both content-based and collaborative interrelationships;   determining, based on the link strengths and at least one venue parameter, a plurality of recommended venues having the strongest links to a user;   generating 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.