Associating People and Documents

Since the introduction of the Enterprise Track at TREC in 2005, the task of finding experts has generated a lot of interest within the research community. Numerous models have been proposed that rank candidates by their level of expertise with respect to some topic. Common to all approaches is a component that estimates the strength of the association between a document and a person. Forming such associations, then, is a key ingredient in expertise search models. In this paper we introduce and compare a number of methods for building document-people associations. Moreover, we make underlying assumptions explicit, and examine two in detail: (i) independence of candidates, and (ii) frequency is an indication of strength. We show that our refined ways of estimating the strength of associations between people and documents leads to significant improvements over the state-of-the-art in the end-to-end expert finding task.