Mining of Massive Datasets 2nd Edition by Leskovec Rajaraman and Ullman

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. 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 can be applied successfully to 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. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent item sets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.

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Bibliographic Information

Title

Mining of Massive Datasets

Author

Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman

Edition

2nd Edition

Publisher

Cambridge University Press

Length

480 pages

ISBN

ISBN-13: 9781107077232

ISBN-10: 1107077230