Generative Modeling of Persons and Documents for Expert Search

Pavel Serdyukov, Djoerd Hiemstra, M.M. Fokkinga, Peter M.G. Apers

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)
19 Downloads (Pure)

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 languageUndefined
Title of host publicationProceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2007)
Place of PublicationNew York, NY, USA
PublisherACM Press
Pages827-828
Number of pages2
ISBN (Print)978-1-59593-597-7
DOIs
Publication statusPublished - Jul 2007
Event30th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007 - Amsterdam, Netherlands
Duration: 23 Jul 200727 Jul 2007
Conference number: 30

Publication series

Name
Number128

Conference

Conference30th Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007
Abbreviated titleSIGIR
CountryNetherlands
CityAmsterdam
Period23/07/0727/07/07

Keywords

  • EWI-10422
  • METIS-241757
  • CR-H.3.3

Cite this

Serdyukov, P., Hiemstra, D., Fokkinga, M. M., & Apers, P. M. G. (2007). Generative Modeling of Persons and Documents for Expert Search. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2007) (pp. 827-828). New York, NY, USA: ACM Press. https://doi.org/10.1145/1277741.1277929