Social network recommended content and recommending members for personalized search results

摘要

Architecture that provides a data structure to facilitate personalized ranking over recommended content (e.g., documents). The data structure approximates the social distance of the searching user to the content at query time. A graph is created of content recommended by members of the social network, where the nodes of the graph include content nodes (for the content) and recommending member nodes (for members of the social network who recommended the content). If a member recommends content, an edge is created between the member node and the content node. If a member is a “friend” (tagged as related in some way) of another member, an edge is created between the two member nodes. Each node is converted to a lower dimensional feature set. Feature sets of the content are indexed and the feature set of the searching user is utilized to match and rank the search results at query time.

主权项

1. A method, comprising:
creating a graph of nodes and node relationships, the graph comprising content nodes of content recommended by members of a social network, entity nodes of the recommending members, and links between the entity nodes according to social links between associated members in the social network, each content node being configured so that the content node (i) does not link to another content node and (ii) links to only a single entity node, the single entity node being the entity node of the recommending member who has recommended the content of the content node; converting each node to a feature set of auxiliary information; sampling some sets of the nodes, the nodes of the sampled sets being seed nodes, each feature set including (i) information about seed nodes closest to the node from which the feature set was converted and (ii) distances to those seed nodes, a distance between a pair of feature sets approximating a social distance between the nodes from which the feature sets were converted; indexing the node relationships for keyword searches that return recommended content of the content nodes; identifying a searching user as associated with the social network; and processing a query against the index using keywords.