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Keyword extraction using an artificial immune system

Published: 07 July 2007 Publication History

Abstract

This paper presents a model for keyword extraction which combines an artificial immune system with a mathematical background based on information theory. The proposed approach does not need any domain knowledge, neither the use of a stopword list. The output is a set of keywords for each of the categories into the corpus used.

References

[1]
Y. Liu, B. J. Ciliax, K. Borges, V. Dasigi, A. Ram, S. B. Navathe, and R. Dingledine. Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering. In CSB. IEEE Computer Society, 2004.
[2]
J. Twycross. An immune system approach to document classification. Technical Report HPL-2002-288, Hewlett Packard Laboratories, 2002.
[3]
I. H. Witten, G. W. Paynter, E. Frank, C. Gutwin, and C. G. Nevill--Manning. KEA: Practical automatic keyphrase extraction. CoRR, cs.DL/9902007, 1999.

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    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 07 July 2007

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    Author Tags

    1. artificial immune systems
    2. information theory
    3. keyword extraction

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    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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