The text mining handbook
advanced approaches in analyzing unstructured data
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Author
Contributions
- Sanger, James, 1965- - Contributor
Publication
2006 - Cambridge University Press, New York, New York (State)
Language
English
Word Count
102,500 words, Guess
Page Count
410 pages
Identifiers
- Open LibraryOL3413203M
- ISBN-100521836573
- OCLC Control Number61881155
- OCLC Control Numbertextmininghandbo00feld_909
- Library of Congress Control Number2005029330
and 2 more
- LibraryThing2160665
- Goodreads893219
Classifications
- DDC005.74
- LCCQA76.9.D343 F45 2006
Description
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 CfI a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining CfI 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.
Subjects
Topics
Genres
- Handbooks, manuals, etc.
Other Editions
- The text mining handbook: advanced approaches in analyzing unstructured data
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