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The text mining handbook : advanced approaches in analyzing unstructured data / Ronen Feldman, James Sanger.

By: Contributor(s): Material type: TextTextPublication details: Cambridge ; New York : Cambridge University Press, 2007.Description: xii, 410 p. : ill. ; 27 cmISBN:
  • 9780521836579
Subject(s): DDC classification:
  • 005.74   22
Contents:
Summary: Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it 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.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Books Books Main library General Stacks 005.74 / FE.T 2007 (Browse shelf(Opens below)) 1 Available 001094
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005.74 / CO.B 2008 Business database systems / 005.74 / CO.D 2010 Database systems : 005.74 / EL.F 2007 Fundamentals of database systems / 005.74 / FE.T 2007 The text mining handbook : 005.74 / GA.D 2009 Database systems : 005.74 / JE.E 2006 Expert one-on-one Visual BASIC 2005 database programming / 005.74 / KR.D 2008 Database concepts /

Includes bibliographical references (p. 335-387) and index.

Introduction to text mining -- Core text mining operations -- Text mining preprocessing techniques -- Categorization -- Clustering -- Information extraction -- Probabilistic models for information extraction -- Preprocessing applications using probabilistic and hybrid approaches -- Presentation-layer considerations for browsing and query refinement -- Visualization approaches -- Link analysis -- Text mining applications.

Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it 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.

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