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 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 Clinton Gormley, Zachary Tong - O'Reilly
Whether you need full-text search or real-time analytics of data, this book introduces you to the fundamental concepts required to start working with Elasticsearch. With these foundations laid, it will move on to more-advanced search techniques.
by David Maier - Computer Science Press
The book is intended for a second course in databases and a reference for researchers in the field. The material covered includes relational algebra, functional dependencies, multivalued and join dependencies, normal forms, representation theory...
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.