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Pattern Mining with Natural Language Processing: An Exploratory Approach

  • Ana Cristina Mendes
  • Cláudia Antunes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5632)

Abstract

Pattern mining derives from the need of discovering hidden knowledge in very large amounts of data, regardless of the form in which it is presented. When it comes to Natural Language Processing (NLP), it arose along the humans’ necessity of being understood by computers. In this paper we present an exploratory approach that aims at bringing together the best of both worlds. Our goal is to discover patterns in linguistically processed texts, through the usage of NLP state-of-the-art tools and traditional pattern mining algorithms.

Articles from a Portuguese newspaper are the input of a series of tests described in this paper. First, they are processed by an NLP chain, which performs a deep linguistic analysis of text; afterwards, pattern mining algorithms Apriori and GenPrefixSpan are used. Results showed the applicability of sequential pattern mining techniques in textual structured data, and also provided several evidences about the structure of the language.

Keywords

Association Rule Natural Language Processing Minimum Support Pattern Mining Parse Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ana Cristina Mendes
    • 1
  • Cláudia Antunes
    • 2
  1. 1.Spoken Language Systems Laboratory - L2F/INESC-ID Instituto Superior TécnicoTechnical University of LisbonLisboaPortugal
  2. 2.Department of Computer Science and Engineering Instituto Superior TécnicoTechnical University of LisbonLisboaPortugal

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