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Concept-Based Text Mining
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Author(s): Stanley Loh (Lutheran University of Brazil, Brazil), Leandro Krug Wives (Federal University of Rio Grande do Sul, Brazil), Daniel Lichtnow (Catholic University of Pelotas, Brazil)and José Palazzo M. de Oliveira (Federal University of Rio Grande do Sul, Brazil)
Copyright: 2009
Pages: 13
Source title:
Handbook of Research on Text and Web Mining Technologies
Source Author(s)/Editor(s): Min Song (New Jersey Institute of Technology, USA)and Yi-Fang Brook Wu (New Jersey Institute of Technology, USA)
DOI: 10.4018/978-1-59904-990-8.ch021
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Abstract
The goal of this chapter is to present an approach to mine texts through the analysis of higher level characteristics (called “concepts’), minimizing the vocabulary problem and the effort necessary to extract useful information. Instead of applying text mining techniques on terms or keywords labeling or extracted from texts, the discovery process works over concepts extracted from texts. Concepts represent real world attributes (events, objects, feelings, actions, etc.) and, as seen in discourse analysis, they help to understand ideas and ideologies present in texts. A previous classification task is necessary to identify concepts inside the texts. After that, mining techniques are applied over the concepts discovered. The chapter will discuss different concept-based text mining techniques and present results from different applications.
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