Automatic Acknowledgement Indexing: Expanding the Semantics of Contribution in the CiteSeer Digital Library


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

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oaioai:CiteSeerX.psu: time updated on 10/22/2014

This paper was published in CiteSeerX.

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