Survey of Text Mining: No. 1 : Clustering, Classification, and Retrieval
Survey of Text Mining: No. 1 : Clustering, Classification, and Retrieval

Survey of Text Mining: No. 1 : Clustering, Classification, and Retrieval.cMichael J. A. Berry
Survey of Text Mining: No. 1 : Clustering, Classification, and Retrieval
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Author: Michael J. A. Berry
Number of Pages: 261 pages
Published Date: 09 Sep 2003
Publisher: Springer-Verlag New York Inc.
Publication Country: New York, NY, United States
Language: English
Format: PDF
ISBN: 9780387955636
File size: 41 Mb
File Name: Survey.of.Text.Mining.No..1.Clustering,.Classification,.and.Retrieval.pdf
Download Link: Survey of Text Mining No. 1 Clustering, Classification, and Retrieval
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Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

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