Data Mining Desktop Survival Guide
by Graham Williams
Publisher: Togaware Pty Ltd 2004
Data mining is about building models from data. We build models to gain insights into the world and how the world works. A data miner, in building models, deploys many different data analysis and model building techniques. Our choices depend on the business problems to be solved. Although data mining is not the only approach it is becoming very widely used because it is well suited to the data environments we find in today's enterprises.
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by Christian S. Jensen - Aalborg University
Topics covered: the semantics of temporal data, the design of data models and languages for temporal data, the design of databases expressed in terms of temporal data models as well as temporally enhanced design of conventional databases.
by Jimmy Lin, Chris Dyer - Morgan & Claypool Publishers
This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns.
by Ron Zacharski - GuideToDatamining.com
Before you is a tool for learning basic data mining techniques. If you are a programmer interested in learning a bit about data mining you might be interested in a beginner's hands-on guide as a first step. That's what this book provides.
by S. Yuan, A.Z. Abidin, M. Sloan, J. Wang - arXiv
A comprehensive survey on Internet advertising, discussing the research issues, identifying the recent technologies, and suggesting its future directions. We start with a brief history, introduction, and classification of the industry.