Text mining : classification, clustering, and applications

Contributor(s): Srivastava, Ashok, (Editor) | Sahami, Mehran. (Editor)Material type: TextTextSeries: Chapman & Hall/CRC data mining and knowledge discovery seriesPublication details: Boca Raton, FL : CRC Press, 2009Description: xxx, 290 p. : illISBN: 9781420059403 (hardcover : alk. paper); 1420059408Subject(s): Data mining | Data mining -- Statistical methodsDDC classification: 006.31
Contents:
Analysis of text patterns using kernel methods / Marco Turchi, Alessia Mammone, Nello Cristianini -- Detection of bias in media outlets with statistical learning methods / Blaz Fortuna, Carolina Galleguillos, Nello Cristianini -- Collective classification for text classification / Galileo Namata [and others] -- Topic models / David M. Blei, John D. Lafferty -- Nonnegative matrix and tensor factorization for discussion tracking / Brett W. Bader, Michael W. Berry, Amy N. Langville -- Text clustering with mixture of von Mises-Fisher distributions / Arindam Banerjee [and others] -- Constrained partitional clustering of text data: an overview / Sugato Basu, Ian Davidson -- Adaptive information filtering / Yi Zhang -- Utility-based information distillation / Yiming Yang, Abhimanyu Lad -- Text search-enhanced with types and entities / Soumen Chakrabarti [and others].
Summary: Giving a broad perspective of the field from numerous vantage points, 'Text Mining' 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
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Reference 		Reference 006.31 TEX (Browse shelf(Opens below)) Available 015462
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Includes index

Analysis of text patterns using kernel methods / Marco Turchi, Alessia Mammone, Nello Cristianini --
Detection of bias in media outlets with statistical learning methods / Blaz Fortuna, Carolina Galleguillos, Nello Cristianini --
Collective classification for text classification / Galileo Namata [and others] --
Topic models / David M. Blei, John D. Lafferty --
Nonnegative matrix and tensor factorization for discussion tracking / Brett W. Bader, Michael W. Berry, Amy N. Langville --
Text clustering with mixture of von Mises-Fisher distributions / Arindam Banerjee [and others] --
Constrained partitional clustering of text data: an overview / Sugato Basu, Ian Davidson --
Adaptive information filtering / Yi Zhang --
Utility-based information distillation / Yiming Yang, Abhimanyu Lad --
Text search-enhanced with types and entities / Soumen Chakrabarti [and others].

Giving a broad perspective of the field from numerous vantage points, 'Text Mining' 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

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