Ranking experts using author-document-topic graphs

Das G. Sujatha, Prasenjit Mitra, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

Expert search or recommendation involves the retrieval of people (experts) in response to a query and on occasion, a given set of constraints. In this paper, we address expert recommendation in academic domains that are different from web and intranet environments studied in TREC. We propose and study graph-based models for expertise retrieval with the objective of enabling search using either a topic (e.g. "Information Extraction") or a name (e.g. "Bruce Croft"). We show that graph-based ranking schemes despite being "generic" perform on par with expert ranking models specific to topic-based and name-based querying.

Original languageEnglish
Title of host publicationJCDL 2013 - Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries
Pages87-96
Number of pages10
DOIs
Publication statusPublished - 23 Aug 2013
Event13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2013 - Indianapolis, IN, United States
Duration: 22 Jul 201326 Jul 2013

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)1552-5996

Conference

Conference13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2013
CountryUnited States
CityIndianapolis, IN
Period22/7/1326/7/13

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Keywords

  • Author-document-topic graphs
  • Expert search
  • Pagerank
  • Similar expert finding

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Sujatha, D. G., Mitra, P., & Lee Giles, C. (2013). Ranking experts using author-document-topic graphs. In JCDL 2013 - Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries (pp. 87-96). (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries). https://doi.org/10.1145/2467696.2467707