Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
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Published By Elsevier

9780123869791

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Text Mining for Patterns in Children’s Sleep Disorders Using STATISTICA Text Miner

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00015-3 ◽

2012 ◽

pp. 357-374

Author(s):

Jennifer Thompson ◽

Karen Spruyt

Keyword(s):

Text Mining ◽

Sleep Disorders ◽

Children’S Sleep

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Classifying Documents with Respect to “Earnings” and Then Making a Predictive Model for the Target Variable Using Decision Trees, MARSplines, Naïve Bayes Classifier, and K-Nearest Neighbors with STATISTICA Text Miner

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00032-3 ◽

2012 ◽

pp. 773-796

Keyword(s):

Predictive Model ◽

Decision Trees ◽

Naive Bayes ◽

Nearest Neighbors ◽

Naïve Bayes ◽

Naive Bayes Classifier ◽

Bayes Classifier ◽

Naïve Bayes Classifier ◽

Target Variable ◽

K Nearest Neighbors

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The History of Text Mining

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00001-3 ◽

2012 ◽

pp. 3-27

Keyword(s):

Text Mining ◽

History Of

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Clustering Words and Documents

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00041-4 ◽

2012 ◽

pp. 959-966

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Analysis of Survey Data for Establishing the “Best Medical Survey Instrument” Using Text Mining

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00012-8 ◽

2012 ◽

pp. 233-249

Author(s):

Jeremy LaMotte ◽

Ruth Moore ◽

Sanjay Thomas ◽

Chris Jenkins ◽

Linda A. Miner

Keyword(s):

Text Mining ◽

Survey Data ◽

Survey Instrument

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Case Study

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00007-4 ◽

2012 ◽

pp. 127-131 ◽

Cited By ~ 1

Author(s):

Tom Emerson ◽

Rishab Ghosh ◽

Eddie Smith

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Singular Value Decomposition in Text Mining

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00039-6 ◽

2012 ◽

pp. 935-947

Keyword(s):

Text Mining ◽

Singular Value Decomposition ◽

Singular Value ◽

Value Decomposition

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Foreword 1

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.06001-1 ◽

2012 ◽

pp. xv-xvi

Author(s):

Peter A. Lachenbruch

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Predicting Box Office Success of Motion Pictures with Text Mining

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00023-2 ◽

2012 ◽

pp. 543-556

Author(s):

Dursun Delen

Keyword(s):

Text Mining ◽

Motion Pictures ◽

Box Office

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Case Study

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications ◽

10.1016/b978-0-12-386979-1.00021-9 ◽

2012 ◽

pp. 509-532

Author(s):

Olivier Jouve ◽

Eric Martin ◽

Marie-Claude Guerin

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Practical Text Mining and Statistical Analysis for Non-structured Text Data ApplicationsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Elsevier

Text Mining for Patterns in Children’s Sleep Disorders Using STATISTICA Text Miner

Classifying Documents with Respect to “Earnings” and Then Making a Predictive Model for the Target Variable Using Decision Trees, MARSplines, Naïve Bayes Classifier, and K-Nearest Neighbors with STATISTICA Text Miner

The History of Text Mining

Clustering Words and Documents

Analysis of Survey Data for Establishing the “Best Medical Survey Instrument” Using Text Mining

Case Study

Singular Value Decomposition in Text Mining

Foreword 1

Predicting Box Office Success of Motion Pictures with Text Mining

Case Study

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
Latest Publications