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Usefulness of click-through data in expert search
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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval table of contents
Boston, MA, USA
POSTER SESSION: Posters table of contents
Pages 816-817  
Year of Publication: 2009
ISBN:978-1-60558-483-6
Authors
Craig Macdonald  University of Glasgow, Glasgow, United Kingdom
Ryen W. White  Microsoft Research, Redmond, WA, USA
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The task in expert finding is to identify members of an organisation with relevant expertise on a given topic. Typically, an expert search engine uses evidence from the authors of on-topic documents found in the organisation's intranet by search engines. The search result click-through behaviour of many intranet search engine users provides an additional source of evidence to identify topically-relevant documents, and via document authorship, experts. In this poster, we assess the usefulness of click-through log data for expert finding. We find that ranking authors based solely on the clicks their documents receive is reasonably effective at correctly identifying relevant experts. Moreover, we show that this evidence can successfully be integrated with an existing expert search engine to increase its retrieval effectiveness.



Collaborative Colleagues:
Craig Macdonald: colleagues
Ryen W. White: colleagues