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The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data (Hardback)
  • The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data (Hardback)
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The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data (Hardback)

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£62.99
Hardback 424 Pages / Published: 11/12/2006
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Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection - a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining - also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.

Publisher: Cambridge University Press
ISBN: 9780521836579
Number of pages: 424
Weight: 950 g
Dimensions: 254 x 178 x 24 mm


MEDIA REVIEWS
' ... buy the book. This book is definitely worth having in your book shelf as a handy reference.' IAPR Newsletter
"...buy the book. This book is definitely worth having in your book shelf as a handy reference." L. Venkata Subramaniam IAPR Newsletter
"A good introduction to text mining written by leading experts in the field. The book is well written and addresses both the theory and practice of text mining, which makes it appealing for researchers and practitioners alike... Highly recommended to those who would like to start delving into the area of text mining without having any previous background in computational linguistics." Rada Mihalcea, University of North Texas, for Computational Linguistics

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