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Zhu, Jianhan; Song, Dawei; Rüger, Stefan; Eisenstadt, Marc and Motta, Enrico
(2006).
URL: http://trec.nist.gov/pubs/trec15/papers/openu.ent....
Abstract
The Multimedia and Information Systems group at the Knowledge Media Institute of the Open University participated in the Expert Search task of the Enterprise Track in TREC 2006. We have proposed to address three main innovative points in a two-stage language model, which consists of a document relevance model and a cooccurrence model, in order to improve the performance of expert search. The three innovative points are based on characteristics of documents. First, document authority in terms of their PageRanks is considered in the document relevance model. Second, document internal structure is taken into account in the co-occurrence model. Third, we consider multiple levels of associations between experts and query terms in the co-occurrence model. Our experiments on the TREC2006 Expert Search task show that addressing the above three points has led to improved effectiveness of expert search on the W3C dataset.
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- Item ORO ID
- 36078
- Item Type
- Conference or Workshop Item
- Extra Information
- Proc. of The Fifteenth Text REtrieval Conference (TREC 2006), Gaithersburg, Maryland USA, National Institute of Standards and Technology, USA
- Academic Unit or School
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Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications - Research Group
- Centre for Research in Computing (CRC)
- Copyright Holders
- © 2006 Not known
- Related URLs
- Depositing User
- Danielle Lilly