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US 2006/0190225 A1Published application
Collaborative filtering using random walks of Markov chains
OwnerMatthew Brandinventor
Life of this patent
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Abstract
A collaborative filtering method first converts a relational database to a graph of nodes connected by edges. The relational database includes consumer attributes, product attributes, and product ratings. Statistics of a Markov chain random walk on the graph are determined. Then, in response to a query state, states of the Markov chain are determined according to the statistics to make a recommendation.
Claims11
A computer implemented method for collaborative filtering, comprising:
- converting a relational database to a graph of nodes connected by edges, the relational database including consumer attributes, product attributes, and product ratings;
- determining statistics of a Markov chain random walk on the graph;
- and
- sorting, in response to a query state, states of the Markov chain according to the statistics to make a recommendation.
1 more element
A collaborative filtering system, comprising:
- a relational database including consumer attributes, product attributes, and product ratings;
- a graph of nodes connected by edges derived from the relational database;
- statistics of a Markov chain random walk on the graph;
- and
- means for sorting, in response to a query state, states of the Markov chain according to the statistics to make a recommendation
2 more elements
Dependencies are inferred from the claim text.