Modeling Expert Finding as an Absorbing Random Walk

Pavel Serdyukov; H. Rode; Djoerd Hiemstra

doi:10.1145/1390334.1390509

Modeling Expert Finding as an Absorbing Random Walk

Pavel Serdyukov, H. Rode, Djoerd Hiemstra

Databases (Former)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

12 Citations (Scopus)

179 Downloads (Pure)

Abstract

We introduce a novel approach to expert nding based on multi-step relevance propagation from documents to related candidates. Relevance propagation is modeled with an ab- sorbing random walk. The evaluation on the two ocial Enterprise TREC data sets demonstrates the advantage of our method over the state-of-the-art method based on one- step propagation.

Original language	Undefined
Title of host publication	Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of Publication	New York
Publisher	Association for Computing Machinery
Pages	797-798
Number of pages	2
ISBN (Print)	978-1-60558-164-4
DOIs	https://doi.org/10.1145/1390334.1390509
Publication status	Published - 20 Jul 2008
Event	31st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008 - Singapore, Singapore Duration: 20 Jul 2008 → 25 Jul 2008 Conference number: 31

Publication series

Name
Publisher	ACM
Number	1

Conference

Conference	31st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008
Abbreviated title	SIGIR
Country/Territory	Singapore
City	Singapore
Period	20/07/08 → 25/07/08

Keywords

EWI-12309
METIS-250963
IR-62256
DB-IR: INFORMATION RETRIEVAL

Access to Document

10.1145/1390334.1390509

http://doi.acm.org/10.1145/1390334.1390509

Cite this

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title = "Modeling Expert Finding as an Absorbing Random Walk",

abstract = "We introduce a novel approach to expert nding based on multi-step relevance propagation from documents to related candidates. Relevance propagation is modeled with an ab- sorbing random walk. The evaluation on the two ocial Enterprise TREC data sets demonstrates the advantage of our method over the state-of-the-art method based on one- step propagation.",

keywords = "EWI-12309, METIS-250963, IR-62256, DB-IR: INFORMATION RETRIEVAL",

author = "Pavel Serdyukov and H. Rode and Djoerd Hiemstra",

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doi = "10.1145/1390334.1390509",

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Serdyukov, P, Rode, H & Hiemstra, D 2008, Modeling Expert Finding as an Absorbing Random Walk. in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval., 10.1145/1390334.1390509, Association for Computing Machinery, New York, pp. 797-798, 31st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008, Singapore, Singapore, 20/07/08. https://doi.org/10.1145/1390334.1390509

Modeling Expert Finding as an Absorbing Random Walk. / Serdyukov, Pavel; Rode, H.; Hiemstra, Djoerd.
Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: Association for Computing Machinery, 2008. p. 797-798 10.1145/1390334.1390509.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - We introduce a novel approach to expert nding based on multi-step relevance propagation from documents to related candidates. Relevance propagation is modeled with an ab- sorbing random walk. The evaluation on the two ocial Enterprise TREC data sets demonstrates the advantage of our method over the state-of-the-art method based on one- step propagation.

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KW - DB-IR: INFORMATION RETRIEVAL

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