03818nam a22005895i 4500 978-3-031-75976-5 DE-He213 20251030114619.0 cr nn 008mamaa 241215s2024 sz | s |||| 0|eng d 9783031759765 978-3-031-75976-5 10.1007/978-3-031-75976-5 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Jo, Taeho. author. aut http://id.loc.gov/vocabulary/relators/aut 88981 Text Mining [electronic resource] : Concepts, Implementation, and Big Data Challenge / by Taeho Jo. 2nd ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XV, 447 p. 368 illus., 147 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Studies in Big Data, 2197-6511 ; 45 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 popular book, updated as a textbook for classroom use, 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. The book features exercises and code to help readers quickly learn and apply knowledge. Presents an array of updated techniques for preprocessing texts into structured forms, geared for classroom use; 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. Computational intelligence. 64052 Telecommunication. Data mining. 6941 Information storage and retrieval systems. 65568 Quantitative research. Computational Intelligence. 64052 Communications Engineering, Networks. Data Mining and Knowledge Discovery. Information Storage and Retrieval. 65570 Data Analysis and Big Data. SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031759758 Printed edition: 9783031759772 Printed edition: 9783031759789 Studies in Big Data, 2197-6511 ; 45 68724 https://doi.org/10.1007/978-3-031-75976-5 ZDB-2-INR ZDB-2-SXIT 65738 65738