Ranking authors in digital libraries

Sujatha Das Gollapalli, Prasenjit Mitra, C. Lee Giles

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

32 Scopus citations

Abstract

Searching for people with expertise on a particular topic also known as expert search is a common task in digital libraries. Most models for this task use only documents as evidence for expertise while ranking people. In digital libraries, other sources of evidence are available such as a document's association with venues and citation links with other documents. We propose graph-based models that accommodate multiple sources of evidence in a PageRank-like algorithm for ranking experts. Our studies on two publicly-available datasets indicate that our model despite being general enough to be directly useful for ranking other types of objects performs on par with probabilistic models commonly used for expert ranking.

Original languageEnglish (US)
Title of host publicationJCDL'11 - Proceedings of the 2011 ACM/IEEE Joint Conference on Digital Libraries
Pages251-254
Number of pages4
DOIs
StatePublished - Jul 25 2011
Event11th Annual International ACM/IEEE Joint Conference on Digital Libraries, JCDL'11 - Ottawa, ON, Canada
Duration: Jun 13 2011Jun 17 2011

Publication series

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

Other

Other11th Annual International ACM/IEEE Joint Conference on Digital Libraries, JCDL'11
CountryCanada
CityOttawa, ON
Period6/13/116/17/11

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Gollapalli, S. D., Mitra, P., & Giles, C. L. (2011). Ranking authors in digital libraries. In JCDL'11 - Proceedings of the 2011 ACM/IEEE Joint Conference on Digital Libraries (pp. 251-254). (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries). https://doi.org/10.1145/1998076.1998123