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Text mining : applications and theory

Author: Michael W Berry; Jacob Kogan
Publisher: Chichester, U.K. : Wiley, 2010.
Edition/Format:   Print book : Conference publication : EnglishView all editions and formats
Database:WorldCat
Summary:
'Text Mining' addresses best practices in both the art and science of text mining. It covers the theory and application of algorithms and related software that facilitate the extraction and tracking of concepts in textual media.
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Genre/Form: Conference papers and proceedings
Congresses
Material Type: Conference publication
Document Type: Book
All Authors / Contributors: Michael W Berry; Jacob Kogan
ISBN: 9780470749821 0470749822
OCLC Number: 464582516
Description: xiv, 207 pages : illustrations ; 24 cm
Contents: pt. I. Text Extraction, Classification, and Clustering --
Automatic keyword extraction from individual documents --
Algebraic techniques for multilingual document clustering --
Content-based spam email classification using machine-learning algorithms --
Utilizing nonnegative matrix factorization for email classification problems --
Constrained clustering with k-means type algorithms --
pt. II. Anomaly and Trend Detection --
Survey of text visualization techniques --
Adaptive threshold setting for novelty mining --
Text mining and cybercrime --
pt. III. Text Streams --
Events and trends in text streams --
Embedding semantics in LDA topic models.
Responsibility: [editors], Michael W. Berry, Jacob Kogan.

Abstract:

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  Read more...

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"It is extremely useful for practitioners and students in computer science, natural language processing, bioinformatics and engineering who wish to use text mining techniques." (Journal of Read more...

 
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