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Natural Language Information Retrieval pp 75–98Cite as

Combining Corpus Linguistics and Human Memory Models for Automatic Term Association

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Part of the book series: Text, Speech and Language Technology ((TLTB,volume 7))

Abstract

Results of cognitive psychology research are analysed to explain why it is difficult for retrieval system users to bring to mind alternative search terms. A human memory model is modified in such a way that it produces additional search terms instead of human associations. A small experiment shows that such a spreading activation network can find alternative terms — with a performance similar to the normally used similarity measures.

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Author information

Authors and Affiliations

  1. AI Group Institut fuer Informatik, TU Muenchen, Arcisstr. 21, D-80290, Muenchen, Germany

    Gerda Ruge

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  1. Gerda Ruge
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Editor information

Editors and Affiliations

  1. General Electric, Research & Development, 12301, Schenectady, NY, USA

    Tomek Strzalkowski

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© 1999 Springer Science+Business Media Dordrecht

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Ruge, G. (1999). Combining Corpus Linguistics and Human Memory Models for Automatic Term Association. In: Strzalkowski, T. (eds) Natural Language Information Retrieval. Text, Speech and Language Technology, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2388-6_3

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  • DOI: https://doi.org/10.1007/978-94-017-2388-6_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5209-4

  • Online ISBN: 978-94-017-2388-6

  • eBook Packages: Springer Book Archive

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