Text mining : concepts, implementation, and big data challenge
Author(s)
Bibliographic Information
Text mining : concepts, implementation, and big data challenge
（Studies in big data, v. 45）
Springer, c2019
Available at 3 libraries
Note
Includes bibliographical references (p. 359-363) and index
Description and Table of Contents
Description
This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.
Table of Contents
Part I: Foundation1 Introduction2 Text Indexing3 Text Encoding4 Text AssociationPart II: Text Categorization5 Text Categorization: Conceptual View6 Text Categorization: Approaches7 Text Categorization: Implementation8 Text Categorization: EvaluationPart III: Text Clustering9 Text Clustering: Conceptual View10 Text Clustering: Approaches11 Text Clustering: Implementation12 Text Clustering: EvaluationPart IV: Advanced Topics13 Text Summarization14 Text Segmentation15 Taxonomy Generation16 Dynamic Document OrganizationReferencesIndex
by "Nielsen BookData"