Natural Language Processing and Text Mining

Author:   Anne Kao ,  Steve R. Poteet
Publisher:   Springer London Ltd
Edition:   Softcover reprint of hardcover 1st ed. 2007
ISBN:  

9781849965583


Pages:   265
Publication Date:   13 October 2010
Format:   Paperback
Availability:   In Print   Availability explained
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Natural Language Processing and Text Mining


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Full Product Details

Author:   Anne Kao ,  Steve R. Poteet
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   Softcover reprint of hardcover 1st ed. 2007
Dimensions:   Width: 15.50cm , Height: 1.40cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9781849965583


ISBN 10:   1849965587
Pages:   265
Publication Date:   13 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Overview.- Extracting Product Features and Opinions from Reviews.- Extracting Relations from Text: From Word Sequences to Dependency Paths.- Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles.- A Case Study in Natural Language Based Web Search.- Evaluating Self-Explanations in iSTART: Word Matching, Latent Semantic Analysis, and Topic Models.- Textual Signatures: Identifying Text-Types Using Latent Semantic Analysis to Measure the Cohesion of Text Structures.- Automatic Document Separation: A Combination of Probabilistic Classification and Finite-State Sequence Modeling.- Evolving Explanatory Novel Patterns for Semantically-Based Text Mining.- Handling of Imbalanced Data in Text Classification: Category-Based Term Weights.- Automatic Evaluation of Ontologies.- Linguistic Computing with UNIX Tools.

Reviews

From the reviews: The papers in this book describe a range of natural language processing (NLP) techniques and applications, all originating from an ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) panel discussion. ! Overall, the contributions are well balanced with respect to the different approaches presented ! . The volume appears to serve its intended purpose, which is to provide an electric overview of the international research efforts in text mining, featuring relevant tools and techniques from NLP and machine learning. (Peter Jackson, Computing Reviews, March, 2008)


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