Multi-Relational Data Mining
by Arno Jan Knobbe
Publisher: IOS Press 2006
Number of pages: 130
This thesis is concerned with Data Mining: extracting useful insights from large and detailed collections of data. With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, this subject has become of increasing importance.
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by Saed Sayad - University of Toronto
Data Mining is about explaining the past and predicting the future by means of data analysis. Data mining is a multidisciplinary field which combines statistics, machine learning, artificial intelligence and database technology.
by Anand Rajaraman, Jeffrey D. Ullman - Stanford University
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.
by 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.
- National Academies Press
Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products.