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Mining of massive datasets/

By: Contributor(s): Material type: TextTextPublication details: Delhi: Cambridge University Press, 2014Edition: 2nd edDescription: xi, 467pISBN:
  • 9781316638491
Subject(s): DDC classification:
  • 006.312 LES
Summary: 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.
Item type: Book
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Item type Current library Call number Status Date due Barcode
Book Book IIM Kashipur 006.312 LES (Browse shelf(Opens below)) Available 8809

Includes index.

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.

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