Patent ID: 9406021
Filing Date: 2016-08-02
CPC Classification: G06N,G06Q

Claim Text:
1. A method of predicting a relation between entities comprising: constructing, at a computer device, a heterogeneous graph representation of multi-source data including: receiving data for forming multiple unipartite sub-graphs, each sub-graph having homogeneous vertices and edges connecting said vertices, and receiving data for forming bipartite sub-graphs having partially observed edges connecting respective nodes between any two different unipartite sub-graphs, said partially observed edges representing cross-entity links; computing at said computer device, a steady-state relevance matrix for each sub-graph using a homogeneous Markov Random Walk model applied to each said unipartite sub-graph; dynamically generating missing edges connecting vertices between each of two unipartite sub-graphs by applying, using said computed steady-state relevance matrix for each sub-graph, an iterative and heterogeneous Markov Random Walk model to said bipartite sub-graphs to dynamically generate missing edges, wherein a generated missing edge represents a cross-entity connection recommendation or prediction in said heterogeneous graph, wherein a programmed processor unit of said computer device performs said receiving, constructing, applying said first Markov Random Walk model to each said unipartite sub-graph and applying said iterative Markov Random Walk model to said bipartite sub-graphs.