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Automatic Acknowledgement Indexing: Expanding the Semantics of Contribution in the CiteSeer Digital Library (2005)
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| Venue: | INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE |
| Citations: | 6 - 3 self |
BibTeX
@INPROCEEDINGS{Councill05automaticacknowledgement,
author = {Isaac G. Councill and C. Lee Giles and Hui Han and Eren Manavoglu},
title = {Automatic Acknowledgement Indexing: Expanding the Semantics of Contribution in the CiteSeer Digital Library},
booktitle = {INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE},
year = {2005},
pages = {19--26},
publisher = {ACM}
}
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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.
Keyphrases
citeseer digital library automatic acknowledgement indexing citeseer system relative impact manual information extraction support vector machine influential contribution large-scale acknowledgement analysis scientific work research publication traditional metadata research document regular expression mixture method autonomous citation indexing acknowledged entity extraction result high cost top twenty citation index
