Details
Original language | English |
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Title of host publication | Advances in Information Retrieval |
Subtitle of host publication | 29th European Conference on IR Research, ECIR 2007, Proceedings |
Publisher | Springer Verlag |
Pages | 737-740 |
Number of pages | 4 |
ISBN (electronic) | 978-3-540-71496-5 |
ISBN (print) | 978-3-540-71494-1 |
Publication status | Published - 2007 |
Event | 29th European Conference on IR Research, ECIR 2007 - Rome, Italy Duration: 2 Apr 2007 → 5 Apr 2007 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 4425 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (electronic) | 1611-3349 |
Abstract
An expert finding is a very common task among enterprise search activities, while its usual retrieval performance is far from the quality of the Web search. Query modeling helps to improve traditional document retrieval, so we propose to apply it in a new setting. We adopt a general framework of language modeling for expert finding. We show how expert language models can be used for advanced query modeling. A preliminary experimental evaluation on TREC Enterprise Track 2006 collection shows that our method improves the retrieval precision on the expert finding task.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Advances in Information Retrieval: 29th European Conference on IR Research, ECIR 2007, Proceedings. Springer Verlag, 2007. p. 737-740 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4425 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Enhancing expert search through query modeling
AU - Serdyukov, Pavel
AU - Chernov, Sergey
AU - Nejdl, Wolfgang
PY - 2007
Y1 - 2007
N2 - An expert finding is a very common task among enterprise search activities, while its usual retrieval performance is far from the quality of the Web search. Query modeling helps to improve traditional document retrieval, so we propose to apply it in a new setting. We adopt a general framework of language modeling for expert finding. We show how expert language models can be used for advanced query modeling. A preliminary experimental evaluation on TREC Enterprise Track 2006 collection shows that our method improves the retrieval precision on the expert finding task.
AB - An expert finding is a very common task among enterprise search activities, while its usual retrieval performance is far from the quality of the Web search. Query modeling helps to improve traditional document retrieval, so we propose to apply it in a new setting. We adopt a general framework of language modeling for expert finding. We show how expert language models can be used for advanced query modeling. A preliminary experimental evaluation on TREC Enterprise Track 2006 collection shows that our method improves the retrieval precision on the expert finding task.
UR - http://www.scopus.com/inward/record.url?scp=37149052555&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-71496-5_81
DO - 10.1007/978-3-540-71496-5_81
M3 - Conference contribution
AN - SCOPUS:37149052555
SN - 978-3-540-71494-1
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 737
EP - 740
BT - Advances in Information Retrieval
PB - Springer Verlag
T2 - 29th European Conference on IR Research, ECIR 2007
Y2 - 2 April 2007 through 5 April 2007
ER -