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Autonomous and Adaptive Identification of Topics in Unstructured Text

  • Conference paper
Book cover Knowlege-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6882))

Abstract

Existing topic identification techniques must tackle an important problem: they depend on human intervention, thus incurring major preparation costs and lacking operational flexibility when facing novelty. To resolve this issue, we propose an adaptable and autonomous algorithm that discovers topics in unstructured text documents. The algorithm is based on principles that differ from existing natural language processing and artificial intelligence techniques. These principles involve the retrieval, activation and decay of general-purpose lexical knowledge, inspired by how the brain may process information when someone reads. The algorithm handles words sequentially in a single document, contrary to the usual corpus-based bag-of-words approach. Empirical results demonstrate the potential of the new algorithm.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, Royal Military College, Kingston, Canada, K7K 7B4

    Louis Massey

Authors
  1. Louis Massey
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Editor information

Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Sakai,, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Adelaide, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2011 Springer-Verlag Berlin Heidelberg

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Massey, L. (2011). Autonomous and Adaptive Identification of Topics in Unstructured Text. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_1

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  • DOI: https://doi.org/10.1007/978-3-642-23863-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23862-8

  • Online ISBN: 978-3-642-23863-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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