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Towards a text mining methodology using association rule extraction

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Abstract

This paper proposes a methodology for text mining relying on the classical knowledge discovery loop, with a number of adaptations. First, texts are indexed and prepared to be processed by frequent itemset levelwise search. Association rules are then extracted and interpreted, with respect to a set of quality measures and domain knowledge, under the control of an analyst. The article includes an experimentation on a real-world text corpus holding on molecular biology.

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Authors and Affiliations

  1. LORIA (CNRS – INRIA – Nancy universities), Campus scientifique, BP 239, Vandœuvre-lès-Nancy, 54506, France

    H. Cherfi, A. Napoli & Y. Toussaint

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  1. H. Cherfi
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  2. A. Napoli
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  3. Y. Toussaint
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Correspondence to H. Cherfi.

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Cherfi, H., Napoli, A. & Toussaint, Y. Towards a text mining methodology using association rule extraction. Soft Comput 10, 431–441 (2006). https://doi.org/10.1007/s00500-005-0504-x

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