Automatic acknowledgement indexing: Expanding the semantics of contribution in the CiteSeer digital library

Isaac G. Councill, C. Lee Giles, Hui Han, Eren Manavoglu

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

10 Scopus citations

Abstract

Acknowledgements in research publications, like citations, indicate influential contributions to scientific work; however, large-scale acknowledgement analyses have traditionally been impractical due to the high cost of manual information extraction. In this paper we describe a mixture method for automatically mining acknowledgements from research documents using a combination of a Support Vector Machine and regular expressions. The algorithm has been implemented as a plug-in to the CiteSeer Digital Library and the extraction results have been integrated with the traditional metadata and citation index of the CiteSeer system. As a demonstration, we use CiteSeer's autonomous citation indexing (ACI) feature to measure the relative impact of acknowledged entities, and present the top twenty acknowledged entities within the archive.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd International Conference on Knowledge Capture, K-CAP'05
Pages19-26
Number of pages8
DOIs
StatePublished - Dec 1 2005
Event3rd International Conference on Knowledge Capture, K-CAP'05 - Banff, AB, Canada
Duration: Oct 2 2005Oct 5 2005

Publication series

NameProceedings of the 3rd International Conference on Knowledge Capture, K-CAP'05

Other

Other3rd International Conference on Knowledge Capture, K-CAP'05
CountryCanada
CityBanff, AB
Period10/2/0510/5/05

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Networks and Communications

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