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 Tom Jewett
This text is a teaching resource for an introductory database class at California State University Long Beach, Department of Computer Engineering and Computer Science. It is also designed to be used as an individual self-study tutorial.
by Tony Gill, at al. - Getty Publications
This book provides an overview of metadata, its types, roles, and characteristics; a discussion of metadata as it relates to resources on the Web; a description of methods, tools, standards, and protocols used to publish digital collections; etc.
by E. F. Codd - Addison-Wesley
Written by the originator of the relational model, the book covers the practical aspects of the design of relational databases. The author defines twelve rules that database management systems need to follow in order to be described as relational.
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.