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Text Mining
Details
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
Autorentext
Dr. Taeho Jo The author of this book, Taeho Jo, is the founder of the publishing company, Alpha AI Publication, to which the copyright of this book belongs to, and a professor in KENTECH (Korea Institute of Energy Technology). His specialty is artificial intelligence; he got a Bachelor from Korea University, a Master from POSTECH (Pohang University of Science and Technology), and a PhD from University of Ottawa. He has careers in both industrial organizations, Samsung SDS, ETRI (Electronic and Telecommunication Research Institute), and KISTI (Korea Institute of Science and Technology Information) and academic organizations, Inha University, Hongik University, and KENTECH as a professor. He has published more than 260 research papers and 30 books with almost solo-author, awarded three times in Marquis Who's Who in the World, and granted the noble title, Duke, from United Kingdom in 2018. The author of this book, Taeho Jo, has a very strong vision for the future as a pioneer of artificial intelligence; he recently established the international organization, UAIN (United Artificial Intelligence Nation) for propagating AI techniques globally.
Zusammenfassung
Inhalt
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.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031759758
- Genre Technology Encyclopedias
- Auflage Second Edition 2024
- Lesemotiv Verstehen
- Anzahl Seiten 464
- Herausgeber Springer Nature Switzerland
- Größe H241mm x B160mm x T31mm
- Jahr 2024
- EAN 9783031759758
- Format Fester Einband
- ISBN 3031759753
- Veröffentlichung 15.12.2024
- Titel Text Mining
- Autor Taeho Jo
- Untertitel Concepts, Implementation, and Big Data Challenge
- Gewicht 855g
- Sprache Englisch