Automatic NLP for Competitive Intelligence

Automatic NLP for Competitive Intelligence

Christian Aranha (Pontifical Catholic University of Rio de Janeiro, Brazil) and Emmanuel Passos (Pontifical Catholic University of Rio de Janeiro, Brazil)
Copyright: © 2008 |Pages: 23
DOI: 10.4018/978-1-59904-373-9.ch003
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Abstract

This chapter integrates elements from Natural Language Processing, Information Retrieval, Data Mining and Text Mining to support competitive intelligence. It shows how text mining algorithms can attend to three important functionalities of CI: Filtering, Event Alerts and Search. Each of them can be mapped as a different pipeline of NLP tasks. The chapter goes in-depth in NLP techniques like spelling correction, stemming, augmenting, normalization, entity recognition, entity classification, acronyms and co-reference process. Each of them must be used in a specific moment to do a specific job. All these jobs will be integrated in a whole system. These will be ‘assembled’ in a manner specific to each application. The reader’s better understanding of the theories of NLP provided herein will result in a better ´assembly´.

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