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About Charu C. Aggarwal
HARDCOVER or PDF: https://www.springer.com/gp/book/9783030403430
PDF has better equation formatting than kindle.
(PDF has links, can be used on Kindle reader)
Charu Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He completed his B.Tech. from IIT Kanpur in 1993 and his Ph.D. from Massachusetts Institute of Technology in 1996. He has worked extensively in the field of data mining, with particular interests in data streams, privacy, uncertain data and social network analysis. He has published 19 (8 authored and 11 edited) books, over 400 papers in refereed venues, and has applied for or been granted over 80 patents. His h-index is 103. Because of the commercial value of the above-mentioned patents, he has received several invention achievement awards and has thrice been designated a Master Inventor at IBM. He is a recipient of an IBM Corporate Award (2003) for his work on bio-terrorist threat detection in data streams, a recipient of the IBM Outstanding Innovation Award (2008) for his scientific contributions to privacy technology, and a recipient of an IBM Research Division Award (2008) for his scientific contributions to data stream research. He has received two best paper awards and an EDBT Test-of-Time Award (2014). He has served as the general or program co-chair of the IEEE Big Data Conference (2014), the ICDM Conference (2015), the ACM CIKM Conference (2015), and the KDD Conference (2016). He also co-chaired the data mining track at the WWW Conference 2009. He served as an associate editor of the IEEE Transactions on Knowledge and Data Engineering from 2004 to 2008. He is an action editor of the Data Mining and Knowledge Discovery Journal , an associate editor of the IEEE Transactions on Big Data, and an associate editor of the Knowledge and Information Systems Journal. He is editor-in-chief of the ACM SIGKDD Explorations and is also an editor-in-chief of the ACM Transactions on Knowledge Discovery from Data. He received the IEEE ICDM Research Contributions award in 2015, and the ACM SIGKDD Innovations Award in 2019, which are the two highest awards in the field of data mining. He is a fellow of the SIAM (2015), ACM (2013) and the IEEE (2010) for "contributions to knowledge discovery and data mining techniques."
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Praise for Data Mining: The Textbook -
“As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology
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Comprehensive Coverage of the Entire Area of Classification
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This comprehensive book focuses on three primary aspects of data classification:
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- Domains: The book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm.
- Variations: The book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers.