Mining of Massive Datasets
by Anand Rajaraman, Jeffrey D. Ullman
Publisher: Stanford University 2010
Number of pages: 340
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.
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by Julio Ponce, Adem Karahoca - InTech
This book presents different ways of theoretical and practical advances and applications of data mining in different promising areas. The book will serve as a Data Mining bible to show a right way for the students, researchers and practitioners.
by Hugh Darwen - BookBoon
This book introduces the theory of relational databases, focusing on the application of that theory to the design of computer languages that properly embrace it. The book covers different topics: Types, Variables, Operators, Relational Algebra, etc.
Data mining comprises techniques and algorithms, for determining interesting patterns from large datasets. There are currently hundreds algorithms that perform tasks such as frequent pattern mining, clustering, and classification, among others.
- 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.