11, ISBN: 9781316147047

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 provi… Mehr…

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 impo 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 itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction. General Computing, Computers, Mining of Massive Datasets~~ Anand Rajaraman, Jeffrey David Ullman, Jure Leskovec~~General Computing~~Computers~~9781316147047, en, Mining of Massive Datasets, Anand Rajaraman, Jeffrey David Ullman, Jure Leskovec, 9781316147047, Cambridge University Press, 11/13/2014, , , , Cambridge University Press, 11/13/2014<

ISBN: 9781316147047

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 provi… Mehr…

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 itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction. Digital Content>E-books>Technology>Apple>Other Database Tools, Cambridge University Press Digital >16<

2011, ISBN: 9781316147047

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 provi… Mehr…

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 General Computing, Computers, Mining of Massive Datasets~~ Anand Rajaraman, Jeffrey David Ullman, Jure Leskovec~~General Computing~~Computers~~9781316147047, en, Mining of Massive Datasets, Anand Rajaraman, Jeffrey David Ullman, Jure Leskovec, 9781316147047, Cambridge University Press, 11/13/2014, , , , Cambridge University Press, 11/13/2014<

2014, ISBN: 9781316147047

eBooks, eBook Download (EPUB), Auflage, [PU: Cambridge University Press], [ED: 1], Cambridge University Press, 2014

2014, ISBN: 9781316147047

[ED: 1], Auflage, eBook Download (EPUB), eBooks, [PU: Cambridge University Press]