Tech Reports
Tech Report kmi-07-02 Abstract
The Open University at TREC 2006 Enterprise Track Expert Search Task
Techreport ID: kmi-07-02
Date: 2007
Author(s): Jianhan Zhu, Dawei Song, Stefan Rüger, Marc Eisenstadt, Enrico Motta
The Multimedia and Information Systems group at the Knowledge Media Institute of the Open University par-ticipated 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 co-occurrence 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 experi-ments 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.
Publication(s):
Zhu, J., Song, D., Rüger, S., Eisenstadt, M. and Motta, E. (2006) The Open University at TREC 2006 Enterprise Track Expert Search Task. In Proc. of The Fifteenth Text REtrieval Conference (TREC 2006), Gaithersburg, Maryland USA, National Institute of Standards and Technology, USA
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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