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Mining of Massive Datasets 2nd Edition
출판사 : Cambridge University Press
저 자 : Leskovec
ISBN : 9781107077232
발행일 : 2014-11
도서종류 : 외국도서
발행언어 : 영어
페이지수 : 476
판매가격 : 45,000원
판매여부 : 재고확인요망
253 x 180 x 30 mm :
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Table of Contents

Preface
1. Data mining
2. Map-reduce and the new software stack
3. Finding similar items
4. Mining data streams
5. Link analysis
6. Frequent itemsets
7. Clustering
8. Advertising on the Web
9. Recommendation systems
10. Mining social-network graphs
11. Dimensionality reduction
12. Large-scale machine learning
Index.

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Description Contents Resources Courses About the Authors
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.

Contains brand new material and extended coverage of important topics
Includes a range of over 150 exercises to challenge even the most able student
Slides, homework assignments, project requirements and exams are available from http://infolab.stanford.edu/~ullman/mining/mining.html

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