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 Shigeaki Sakurai (ed.) - InTech
Text mining techniques are studied aggressively in order to extract the knowledge from the data. This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
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 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.
- National Academies Press
Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products.