Advanced Data Mining
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Advanced Data Mining and Applications
Author: Ronghuai Huang
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-07-28
This book constitutes the refereed proceedings of the 5th International Conference on Advanced Data Mining and Applications, ADMA 2009, held in Beijing, China, in August 2009. The 34 revised full papers and 47 revised short papers presented together with the abstract of 4 keynote lectures were carefully reviewed and selected from 322 submissions from 27 countries. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.
Advanced Data Mining and Applications
Author: Xue Li
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-07-26
Here are the proceedings of the 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China, August 2006. The book presents 41 revised full papers and 74 revised short papers together with 4 invited papers. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, and more.
Advanced Data Mining Techniques
Author: David L. Olson
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-01-01
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.