Mining of Massive Datasets by Leskovec, Jure [Hardback]

Description: 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 MapReduce 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 third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

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EAN: 9781108476348

UPC: 9781108476348

ISBN: 9781108476348

MPN: N/A

Item Length: 24.9 cm

Number of Pages: 565 Pages

Language: English

Publication Name: Mining of Massive Datasets

Publisher: Cambridge University Press

Publication Year: 2020

Subject: Computer Science, Management

Item Height: 253 mm

Item Weight: 1240 g

Type: Textbook

Author: Anand Rajaraman, Jure Leskovec, Jeffrey David Ullman

Subject Area: Information Science

Item Width: 178 mm

Format: Hardcover