Query and document models for enterprise search

Open Access
Authors
Publication date 2008
Host editors
  • E.M. Voorhees
  • L.P. Buckland
Book title The Sixteenth Text REtrieval Conference Proceedings (TREC 2007)
Event The Sixteenth Text REtrieval Conference (TREC 2007), Gaithersburg, MD
Pages (from-to) 1-5
Publisher National Institute of Standards and Technology (NIST)
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
We describe our participation in the TREC 2007 Enterprise track and detail our language modeling-based approaches. For document search, our focus was on estimating a mixture model using a standard web collection, and on constructing query models by employing blind relevance feedback and using the example documents provided with the topics. We found that settings performing well on a web collection do not carry over to the CSIRO collection, but the use of advanced query models resulted in significant improvements. In expert search, our experiments concerned document representation, identification of candidate experts, and combinations of expert search strategies. We find no significant difference in average precision but observe small overall positive effects of the advanced models, with large differences between individual topics.
Document type Conference contribution
Published at http://trec.nist.gov/pubs/trec16/papers/uamsterdam-balog.ent.final.pdf
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