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.
Home page url
Download or read it online for free here:
by Adrienne Watt - BCcampus
The purpose of this text is to provide an open source textbook that covers most introductory database courses. This edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, and exercises.
by Eugenia G. Giannopoulou - InTech
This book brings together the most recent advances of data mining research in the promising areas of medicine and biology. It consists of seventeen chapters which describe interesting applications, motivating progress and worthwhile results.
by J. M. Hellerstein, M. Stonebraker - UC Berkeley
These lecture notes provide students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area.
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.