A language modeling framework for expert finding

Balog, K., Azzopardi, L. and de Rijke, M. (2009) A language modeling framework for expert finding. Information Processing and Management, 45(1), pp. 1-19. (doi: 10.1016/j.ipm.2008.06.003)

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Statistical language models have been successfully applied to many information retrieval tasks, including expert finding: the process of identifying experts given a particular topic. In this paper, we introduce and detail language modeling approaches that integrate the representation, association and search of experts using various textual data sources into a generative probabilistic framework. This provides a simple, intuitive, and extensible theoretical framework to underpin research into expertise search. To demonstrate the flexibility of the framework, two search strategies to find experts are modeled that incorporate different types of evidence extracted from the data, before being extended to also incorporate co-occurrence information. The models proposed are evaluated in the context of enterprise search systems within an intranet environment, where it is reasonable to assume that the list of experts is known, and that data to be mined is publicly accessible. Our experiments show that excellent performance can be achieved by using these models in such environments, and that this theoretical and empirical work paves the way for future principled extensions.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Azzopardi, Dr Leif
Authors: Balog, K., Azzopardi, L., and de Rijke, M.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Information Processing and Management
ISSN (Online):1873-5371
Published Online:20 September 2008

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