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Text mining[electronic resource] :classification, clustering, and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3/12
書名/作者:	Text mining : classification, clustering, and applications // Ashok Srivastava, Mehran Sahami.
其他作者:	Srivastava, Ashok,
出版者:	Boca Raton, FL : : CRC Press,, 2009.
面頁冊數:	1 online resource (xxx, 290 p.) : : ill.
標題:	Data Mining.
標題:	Statistics as Topic.
標題:	Data mining - Statistical methods.
ISBN:	9781420059458 (electronic bk.)
ISBN:	1420059459 (electronic bk.)
書目註:	Includes bibliographical references (p. 275) and index.
內容註:	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 ... [et al.] -- 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 ... [et al.] -- 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 ... [et al.].
摘要、提要註:	An extension of data mining, text mining involves the extraction of information and knowledge from unstructured text. This constantly evolving field is increasingly used by major corporations, such as Google, Yahoo, and Microsoft. Featuring contributions from leading researchers in the field, this book provides a detailed overview of text mining theory, applications, and visualization. The theory section discusses text mining, information retrieval, latent semantic analysis, pagerank, latent Dirichlet allocation, and probabilistic relational models. In the section on text mining applications.
電子資源:	http://www.crcnetbase.com/isbn/978-1-4200-5940-3

Text mining[electronic resource] :classification, clustering, and applications /
Text miningclassification, clustering, and applications /[electronic resource] :Ashok Srivastava, Mehran Sahami. - Boca Raton, FL :CRC Press,2009. - 1 online resource (xxx, 290 p.) :ill. - Chapman & Hall/CRC data mining and knowledge discovery series. - Chapman & Hall/CRC data mining and knowledge discovery series..

Includes bibliographical references (p. 275) and 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 ... [et al.] -- 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 ... [et al.] -- 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 ... [et al.].

An extension of data mining, text mining involves the extraction of information and knowledge from unstructured text. This constantly evolving field is increasingly used by major corporations, such as Google, Yahoo, and Microsoft. Featuring contributions from leading researchers in the field, this book provides a detailed overview of text mining theory, applications, and visualization. The theory section discusses text mining, information retrieval, latent semantic analysis, pagerank, latent Dirichlet allocation, and probabilistic relational models. In the section on text mining applications.

ISBN: 9781420059458 (electronic bk.)Subjects--Topical Terms:

559047
Data Mining.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: QA76.9.D343 / T393 2009eb

Dewey Class. No.: 006.3/12

National Library of Medicine Call No.: QA 76.9.D343

Text mining[electronic resource] :classification, clustering, and applications /
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020 $a 1420059459 (electronic bk.)
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020 $z 1420059408 (hbk.)
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245 0 0 $a Text mining $h [electronic resource] : $b classification, clustering, and applications / $c Ashok Srivastava, Mehran Sahami.
260 $a Boca Raton, FL : $b CRC Press, $c 2009.
300 $a 1 online resource (xxx, 290 p.) : $b ill.
490 1 $a Chapman & Hall/CRC data mining and knowledge discovery series
504 $a Includes bibliographical references (p. 275) and index.
505 0 $a 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 ... [et al.] -- 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 ... [et al.] -- 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 ... [et al.].
520 $a An extension of data mining, text mining involves the extraction of information and knowledge from unstructured text. This constantly evolving field is increasingly used by major corporations, such as Google, Yahoo, and Microsoft. Featuring contributions from leading researchers in the field, this book provides a detailed overview of text mining theory, applications, and visualization. The theory section discusses text mining, information retrieval, latent semantic analysis, pagerank, latent Dirichlet allocation, and probabilistic relational models. In the section on text mining applications.
588 $a Description based on print version record.
650 2 $a Data Mining. $3 559047
650 2 $a Statistics as Topic. $3 515555
650 0 $a Data mining $x Statistical methods. $3 559066
655 0 $a Electronic books. $2 local $3 336502
700 1 $a Srivastava, Ashok, $d 1969- $3 559064
700 1 $a Sahami, Mehran. $3 559065
830 0 $a Chapman & Hall/CRC data mining and knowledge discovery series. $3 488186
856 4 0 $u http://www.crcnetbase.com/isbn/978-1-4200-5940-3