Mining of Massive Datasets
Language: English
Published by Cambridge University Press, 2011
- Hardcover
- Used

Seller: World of Books Inc, Montgomery, IL, U.S.A.World of Books Inc
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Condition: Used - Good
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Add to basketItem description from seller
The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.
Seller Inventory # CIN1107015359G
- Title
- Mining of Massive Datasets
- Author
- Anand Rajaraman
- Publisher
- Cambridge University Press
- Publication year
- 2011
- Condition
- Good
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1107015359
- ISBN 13
- 9781107015357
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About the Author
Jeffrey David Ullman is the Stanford W. Ascherman Professor of Computer Science (Emeritus) at Stanford University. He is also the CEO of Gradiance. Ullman's research interests include database theory, data integration, data mining and education using the information infrastructure. He is one of the founders of the field of database theory and was the doctoral advisor of an entire generation of students who later became leading database theorists in their own right. He was also the Ph.D. advisor of Sergey Brin, one of the co-founders of Google, and served on Google's technical advisory board. In 1995 he was inducted as a Fellow of the Association for Computing Machinery and in 2000 he was awarded the Knuth Prize. Ullman is also the co-recipient (with John Hopcroft) of the 2010 IEEE John von Neumann Medal, for 'laying the foundations for the fields of automata and language theory and many seminal contributions to theoretical computer science'.
"About the title" may belong to another edition of this title.
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