A BELIEF NETWORK MODEL FOR EXPERT SEARCH

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

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