A Belief Network Model for Expert Search

Expert search is a task of growing importance in Enterprise settings. In a classical search setting, users normally require relevant documents to fulfil an information need. However, in Enterprise settings, users also have a need to identify the co-workers with relevant expertise to a topic area. An expert search engine assists users with their expertise need, by ranking candidate experts with respect to their predicted expertise about a topic of interest. This work presents a novel model for the expert search, based on a Bayesian belief network. We show how the proposed model can generate several different strategies for ranking candidates by their predicted expertise with respect to a query. The Bayesian belief network model for expert search proposed here is general, as it can be extended in the future to take into account various other types of evidence in the expert search task, such as the social aspect of expert search, where people work within groups and co-author publications.