Mining of Massive Datasets
by Anand Rajaraman, Jeffrey D. Ullman
Publisher: Stanford University 2010
Number of pages: 340
Description:
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.
Download or read it online for free here:
Download link
(2MB, PDF)
Similar books
Natural Language Interfaces to Databases: An Introductionby I. Androutsopoulos, G. D. Ritchie, P. Thanisch - arXiv
This paper is an introduction to natural language interfaces to databases (NLIDBs). Some advantages and disadvantages of NLIDBs are then discussed, comparing NLIDBs to formal query languages, form-based interfaces, and graphical interfaces.
(15547 views)
Forensic Analysis of Database Tamperingby Kyriacos E. Pavlou, Richard T. Snodgrass - University of Arizona
The text on detection via cryptographic hashing. The authors show how to determine when the tampering occurred, what data was tampered, and who did the tampering. Four successively more sophisticated forensic analysis algorithms are presented.
(21312 views)
A Programmer's Guide to Data Miningby Ron Zacharski - GuideToDatamining.com
Before you is a tool for learning basic data mining techniques. If you are a programmer interested in learning a bit about data mining you might be interested in a beginner's hands-on guide as a first step. That's what this book provides.
(10792 views)
Multi-Relational Data Miningby Arno Jan Knobbe - IOS Press
This thesis is concerned with Data Mining: extracting useful insights from large collections of data. With the increased possibilities in modern society for companies and institutions to gather data, this subject has become of increasing importance.
(15702 views)