Emerging Technologies of Text Mining: Techniques and Applications: Techniques and Applications

do Prado, Hercules Antonio, Ferneda, Edilson
IGI Global, 2007 M10 31 - 376 páginas

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.

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here we found information about CENTROID and some functionalities of MEAD.

Páginas seleccionadas


Information Extraction Methodologies and Applications
Creating Strategic Information for Organizations with Structured Text
Automatic NLP for Competitive Intelligence
Mining Profiles and Definitions with Natural Language Processing
Deriving Taxonomy from Documents at Sentence Level
Rule Discovery from Textual Data
Exploring Unclassified Texts Using Multiview Semisupervised Learning
A MultiAgent Neural Network System for Web Text Mining
AntWebWeb Search Based on Ant Behavior Approach and Implementation in Case of Interlegis
Conceptual Clustering of Textual Documents and Some Insights for Knowledge Discovery
A Hierarchical Online Classifier for Patent Categorization
Text Mining to Define a Validated Model of Hospital Rankings
An Interpretation Process for Clustering Analysis Based on the Ontology of Language
Compilation of References
About the Contributors

Contextualized Clustering in Exploratory Web Search

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Términos y frases comunes

Pasajes populares

Página 331 - Giaretta, P. (1995). Ontologies and Knowledge Bases. Towards a Terminological Clarification. In N. Mars (Ed.), Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing (pp.
Página 328 - Deerwester, S., Dumais, ST, Furnas, GW, Landauer, T. K., & Harshman, R. (1990). Indexing By Latent Semantic Analysis.
Página 326 - A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System".
Página 324 - Blum. Empirical support for winnow and weightedmajority based algorithms: results on a calendar scheduling domain.
Página 139 - In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 1997) (pp.
Página 30 - Texts" in Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining held in conjunction with the 17th International Conference on Artificial Intelligence (IJCAI-01), Seattle, August, 2001 12.
Página 335 - Wrapper induction for information extraction. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1997., 1997.
Página 344 - Salton, G. and McGill, MJ (1983). Introduction to Modern Information Retrieval. New York: McGrawHill. Salton, G., Wong, A.

Acerca del autor (2007)

H rcules 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 Bras¡lia. 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 S?o 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 Bras¡lia. He has a D.Sc. in Computer Science from University of Montpellier, France (1992), a M.Sc. in Computer Science from Federal University of Para¡ba, 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. [Editor]

Información bibliográfica