Data Mining: Concepts and Techniques
Not only does the third edition continue the tradition of equipping readers with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field, including data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data.
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Produktdetails
Weitere Autoren: Kamber, Micheline / Pei, Jian
- ISBN: 978-0-12-381479-1
- EAN: 9780123814791
- Produktnummer: 11061986
- Verlag: Elsevier
- Sprache: Englisch
- Erscheinungsjahr: 2017
- Seitenangabe: 703 S.
- Masse: H24.3 cm x B19.6 cm x D4.4 cm 1'772 g
- Auflage: 3rd revised edition.
- Abbildungen: Approx. 150 illustrations
- Gewicht: 1772
Über den Autor
Jiawei Han is Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Well known for his research in the areas of data mining and database systems, he has received many awards for his contributions in the field, including the 2004 ACM SIGKDD Innovations Award. He has served as Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data, and on editorial boards of several journals, including IEEE Transactions on Knowledge and Data Engineering and Data Mining and Knowledge Discovery. Micheline Kamber is a researcher with a passion for writing in easy-to-understand terms. She has a master's degree in computer science (specializing in artificial intelligence) from Concordia University, Canada. Jian Pei is Associate Professor of Computing Science and the director of Collaborative Research and Industry Relations at the School of Computing Science at Simon Fraser University, Canada. In 2002-2004, he was an Assistant Professor of Computer Science and Engineering at the State University of New York (SUNY) at Buffalo. He received a Ph.D. degree in Computing Science from Simon Fraser University in 2002, under Dr. Jiawei Han's supervision.
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