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.
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Mendes, A.C., Antunes, C. (2009). Pattern Mining with Natural Language Processing: An Exploratory Approach. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2009. Lecture Notes in Computer Science(), vol 5632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03070-3_20
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DOI: https://doi.org/10.1007/978-3-642-03070-3_20
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