The task in expert finding is to identify members of an organization with relevant expertise on a given topic. In existing expert finding systems, profiles are constructed from sources such as email or documents, and used as the basis for expert identification. In this paper, we leverage the organizational hierarchy (depicting relationships between managers, subordinates, and peers) to find members for whom we have little or no information. We propose an algorithm to improve expert finding performance by considering not only the expertise of the member, but also the expertise of his or her neighbors. We show that providing this additional information to an expert finding system improves its retrieval performance.
['Maryam Karimzadehgan', 'Ryen W. White', 'Matthew Richardson']
Enhancing Expert Finding Using Organizational Hierarchies