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Conference Papers Year : 2019

RFreeStem: A multilanguage rule-free stemmer


With the large expansion of available textual data, text mining has become of specialinterest. Due to their unstructured nature, such data require important preprocessing steps.Among them, stemming is a popularly used preprocessing method that extracts the root of thewords. However, the most popular algorithms are based on the application of rules, and there-fore highly language-related. We propose a new approach, the RFreeStem, that is rather basedon corpus and can therefore be applied on many languages.
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hal-02891675 , version 1 (07-07-2020)


  • HAL Id : hal-02891675 , version 1
  • OATAO : 26186


Xavier Baril, Oihana Coustié, Josiane Mothe, Olivier Teste. RFreeStem: A multilanguage rule-free stemmer. 37e Congres Informatique des Organisations et Systemes d'Information et de Decision (INFORSID 2019), Jun 2019, Paris, France. pp.12-29. ⟨hal-02891675⟩
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