Overview
- Discusses the process of creating, maintaining, and applying taxonomies via simple, easy-to-understand examples
- Provides a systematic review of the current research frontier of each task and discusses their real-world applications
- Includes supporting materials containing links to commonly used evaluation datasets and a code repository of representative algorithms
Part of the book series: Synthesis Lectures on Data Mining and Knowledge Discovery (SLDMKD)
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Table of contents (6 chapters)
Keywords
About this book
Authors and Affiliations
About the authors
Jiawei Han, Ph.D. is a Michael Aiken Chair Professor at the University of Illinois at Urbana-Champaign. His research areas encompass data mining, text mining, data warehousing, and information network analysis, with over 800 research publications. He is a Fellow of both ACM and the IEEE and has received numerous prominent awards, including the ACM SIGKDD Innovation Award (2004) and the IEEE Computer Society W. Wallace McDowell Award (2009).
Bibliographic Information
Book Title: Automated Taxonomy Discovery and Exploration
Authors: Jiaming Shen, Jiawei Han
Series Title: Synthesis Lectures on Data Mining and Knowledge Discovery
DOI: https://doi.org/10.1007/978-3-031-11405-2
Publisher: Springer Cham
eBook Packages: Synthesis Collection of Technology (R0), eBColl Synthesis Collection 11
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-11404-5Published: 29 September 2022
Softcover ISBN: 978-3-031-11407-6Published: 02 October 2023
eBook ISBN: 978-3-031-11405-2Published: 28 September 2022
Series ISSN: 2151-0067
Series E-ISSN: 2151-0075
Edition Number: 1
Number of Pages: XI, 103
Number of Illustrations: 3 b/w illustrations, 31 illustrations in colour
Topics: Machine Learning, Computer Science, general, Information Storage and Retrieval, Data Mining and Knowledge Discovery, Big Data