Text mining : theoretical aspects and applications
Author(s)
Bibliographic Information
Text mining : theoretical aspects and applications
（Advances in soft computing）
Physica-Verlag, c2003
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Includes bibliographical references and index
Description and Table of Contents
Description
Text Mining - Theoretical Aspects and Applications presents contributions from researchers from different disciplines. Each of them is studying the problem of mining text according to his scientific background: artificial intelligence, computational linguistics, document analysis, machine learning, information retrieval, pattern recognition. Their common goal is to analyse huge text collections in real world applications in order to support knowledge-intensive processes.
Table of Contents
I. Renz, J. Franke: Text Mining.- N. Fuhr: XML Information Retrieval and Information Extraction.- J. Zavrel, W. Daelemans: Feature-Rich Memory-Based Classification for Shallow NLP and Information Extraction.- R. Klinkenberg, S. Ruping: Concept Drift and the Importance of Examples.- T. Joachims: Evaluating Retrieval Performance Using Clickthrough Data.- A. Hust et al.: Towards Collaborative Information Retrieval: Three Approaches.- D. Rosner, M. Kunze: The XDOC Document Suite - a Workbench for Document Mining.- A. Hotho et al.: On Knowledgeable Unsupervised Text Mining.- F. Ceravegna et al.: Using Adaptive Information Extraction for Effective Human-Centred Document Annotation.
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