Abstract
In this paper we address the task of automatically finding an
expert within the organization, known as the expert search
problem. We present the theoretically-based probabilistic
algorithm which models retrieved documents as mixtures
of expert candidate language models. Experiments show
that our approach outperforms existing theoretically sound
solutions.
Original language | Undefined |
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Title of host publication | Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2007) |
Place of Publication | New York, NY, USA |
Publisher | ACM Press |
Pages | 827-828 |
Number of pages | 2 |
ISBN (Print) | 978-1-59593-597-7 |
DOIs | |
Publication status | Published - Jul 2007 |
Event | 30th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007 - Amsterdam, Netherlands Duration: 23 Jul 2007 → 27 Jul 2007 Conference number: 30 |
Publication series
Name | |
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Number | 128 |
Conference
Conference | 30th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007 |
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Abbreviated title | SIGIR |
Country/Territory | Netherlands |
City | Amsterdam |
Period | 23/07/07 → 27/07/07 |
Keywords
- EWI-10422
- METIS-241757
- CR-H.3.3