Emerging Technologies of Text Mining: Techniques and Applications

Emerging Technologies of Text Mining: Techniques and Applications

Hercules Antonio do Prado (Catholic University of Brasilia, Brazil) and Edilson Ferneda (Catholic University of Brasilia, Brazil)
Indexed In: SCOPUS View 1 More Indices
Release Date: October, 2007|Copyright: © 2008 |Pages: 376
DOI: 10.4018/978-1-59904-373-9
ISBN13: 9781599043739|ISBN10: 1599043734|EISBN13: 9781599043753
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Description & Coverage
Description:

Massive amounts of textual data make up most organizations' stored information. Therefore, there is increasingly high demand for a comprehensive resource providing practical hands-on knowledge for real-world applications.

Emerging Technologies of Text Mining: Techniques and Applications provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, Emerging Technologies of Text Mining: Techniques and Applications will provide libraries with the defining reference on this topic.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • AntWeb
  • Automatic NLP
  • Clustering Analysis
  • Competitive Intelligence
  • Conceptual clustering
  • Contextualized clustering
  • Deriving taxonomy
  • Exploring unclassified texts
  • Hierarchical online classifier
  • Information Extraction
  • Knowledge Discovery
  • Mining profiles and definitions
  • Multi-agent neural network system
  • Multi-view semi-supervised learning
  • Natural Language Processing
  • Ontology of language
  • Organizations with structured text
  • Rule discovery
  • Strategic information
  • Text Mining
  • Web text mining
Reviews and Testimonials

This book goes beyond simply showing techniques to generate patterns from texts; it gives the road map to guide the subjective task of patterns interpretation.

– Hercules Antonio do Prado, Catholic University of Brazilia, Brazil
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Editor/Author Biographies
Hércules Antonio do Prado is a researcher in Computer Science at the Brazilian Agricultural Research Corporation (Embrapa Food Technology) and an assistant professor at the Catholic University of Brasília. He received his D.Sc. in Computer Science at the Federal University of Rio Grande do Sul, Brazil (2001) his M.Sc. in Systems Engineering from the Federal University of Rio de Janeiro (1989). In 1999 he joined the Information Sciences Department of University of Pittsburgh as a Visitor Scholar, developing research for his doctoral program. He undergraduated in Computer Systems at the Federal University of São Carlos, Brazil (1976). His research interest includes data/text mining, neural networks, knowledge-based systems, and knowledge management.
Edilson Ferneda is a full professor at the Catholic University of Brasília. He has a D.Sc. in Computer Science from University of Montpellier, France (1992), a M.Sc. in Computer Science from Federal University of Paraíba, Brazil (1988) and undergraduated in Computer Systems at The Aeronautics Technological Institute, Brazil (1979). His research interests include data/text mining, machine learning, knowledge acquisition, knowledge-based systems, CSCL/CSCW, knowledge management and e-learning.
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