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 Chuck Ballard, et al. - IBM Redbooks
It covers data modeling techniques for data warehousing, within the context of the overall data warehouse development process. The process of data warehouse modeling, including the steps required before and after the actual modeling, is discussed.
by 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.
by 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.