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CIKM
2008
Springer

Modeling document features for expert finding

11 years 3 months ago
Modeling document features for expert finding
We argue that expert finding is sensitive to multiple document features in an organization, and therefore, can benefit from the incorporation of these document features. We propose a unified language model, which integrates multiple document features, namely, multiple levels of associations, PageRank, indegree, internal document structure, and URL length. Our experiments on two TREC Enterprise Track collections, i.e., the W3C and CSIRO datasets, demonstrate that the natures of the two organizational intranets and two types of expert finding tasks, i.e., key contact finding for CSIRO and knowledgeable person finding for W3C, influence the effectiveness of different document features. Our work provides insights into which document features work for certain types of expert finding tasks, and helps design expert finding strategies that are effective for different scenarios. Categories and Subject Descriptors H.3 [Information Storage and Retrieval]: H3.1 Content analysis and Indexing; H.3....
Jianhan Zhu, Dawei Song, Stefan M. Rüger, Xia
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CIKM
Authors Jianhan Zhu, Dawei Song, Stefan M. Rüger, Xiangji Huang
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