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Text Mining = Concepts, Implementation, and Big Data Challenge /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Text Mining/ by Taeho Jo.
Reminder of title:	Concepts, Implementation, and Big Data Challenge /
Author:	Jo, Taeho.
Description:	XIII, 373 p. 236 illus., 148 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Electrical engineering. -
Online resource:	https://doi.org/10.1007/978-3-319-91815-0
ISBN:	9783319918150

Text Mining = Concepts, Implementation, and Big Data Challenge /
Jo, Taeho.

Text MiningConcepts, Implementation, and Big Data Challenge /[electronic resource] :by Taeho Jo. - 1st ed. 2019. - XIII, 373 p. 236 illus., 148 illus. in color.online resource. - Studies in Big Data,452197-6503 ;. - Studies in Big Data,8.

Part I: Foundation -- Introduction -- Text Indexing -- Text Encoding -- Text Association -- Part II: Text Categorization -- Text Categorization: Conceptual View -- Text Categorization: Approaches -- Text Categorization: Implementation -- Text Categorization: Evaluation -- Part III: Text Clustering -- Text Clustering: Conceptual View -- Text Clustering: Approaches -- Text Clustering: Implementation -- Text Clustering: Evaluation -- Part IV: Advanced Topics -- Text Summarization -- Text Segmentation -- Taxonomy Generation -- Dynamic Document Organization -- References -- Index.

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. Presents techniques of preprocessing texts into structured forms; Outlines concepts of text categorization and clustering, their algorithms, and implementation guides; Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management.

ISBN: 9783319918150

Standard No.: 10.1007/978-3-319-91815-0doiSubjects--Topical Terms:

596380
Electrical engineering.

LC Class. No.: TK1-9971

Dewey Class. No.: 621.382

Text Mining = Concepts, Implementation, and Big Data Challenge /
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