Text Mining: Classification, Clustering, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) Ashok N. Srivastava

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Published: May 14th 2012

Kindle Edition

328 pages


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Text Mining: Classification, Clustering, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)  by  Ashok N. Srivastava

Text Mining: Classification, Clustering, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) by Ashok N. Srivastava
May 14th 2012 | Kindle Edition | PDF, EPUB, FB2, DjVu, audiobook, mp3, RTF | 328 pages | ISBN: | 5.52 Mb

The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the Field Giving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses onMoreThe Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the Field Giving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis.

It examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas, including adaptive information filtering, information distillation, and text search. The book begins with chapters on the classification of documents into predefined categories. It presents state-of-the-art algorithms and their use in practice.

The next chapters describe novel methods for clustering documents into groups that are not predefined. These methods seek to automatically determine topical structures that may exist in a document corpus. The book concludes by discussing various text mining applications that have significant implications for future research and industrial use. There is no doubt that text mining will continue to play a critical role in the development of future information systems and advances in research will be instrumental to their success.

This book captures the technical depth and immense practical potential of text mining, guiding readers to a sound appreciation of this burgeoning field.



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