Method, system and computer program product for automating expertise management using social and enterprise data

Abstract

A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context. The method can also use the context-specific weights obtained from the co-association information in a matrix completion procedure, and finally merge the context-specific outputs to obtain overall skills predictions, analyses and inferences. A computer program product and a system are also disclosed for performing the method.