Data Mining and Knowledge Discovery

PUBLISHED


Viewing: 1 - 10 of 91
Published:
April 04, 2013
Editor(s):
Ting Yu; Nitesh Chawla; Simeon Simoff
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational 
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Published:
January 28, 2013
Author(s):
Glen Hart; Catherine Dolbear
Geographic Information has an important role to play in linking and combining datasets through shared location, but the potential is still far from fully realized because the data is not well organized and the technology to aid this process has not been available. Developments in the Semantic Web 
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Published:
November 20, 2012
Author(s):
Anang Muhamad Amin; Asad Khan; Benny Nasution
For machine intelligence applications to work successfully, machines must perform reliably under variations of data and must be able to keep up with data streams. Internet-Scale Pattern Recognition: New Techniques for Voluminous Data Sets and Data Clouds unveils computational models that address 
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Published:
November 07, 2012
Author(s):
Norman Fenton; Martin Neil
Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains 
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Published:
November 06, 2012
Author(s):
Sumeet Dua; Pradeep Chowriappa
Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the 
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Published:
October 17, 2012
Author(s):
Boris Mirkin
Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen almost through trial and error. Even the two most popular, and most related, clustering methods—K-Means for partitioning and Ward's method for hierarchical 
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Published:
October 05, 2012
Author(s):
Domenico Talia; Paolo Trunfio
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. 
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Published:
September 07, 2012
Editor(s):
Guozhu Dong; James Bailey
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more 
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Published:
June 13, 2012
Editor(s):
Cameron Lackpour
If you love Essbase and hate seeing it misused, then this is the book for you. Written by 12 Essbase professionals that are either acknowledged Essbase gurus or certified Oracle ACEs, Developing Essbase Applications: Advanced Techniques for Finance and IT Professionals provides an unparalleled 
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Published:
June 06, 2012
Author(s):
Zhi-Hua Zhou
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After 
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Data Mining "Nobel Prize" Awarded to Series Editor Vipin Kumar

The ACM SIGKDD 2012 Innovation Award, the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD), has been awarded to Prof. Vipin Kumar for his technical contributions to foundational research in data mining and its applications to mining scientific and climate data. Prof. Kumar is the editor of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. He has pioneered research in the areas of high performance and parallel data mining. His research group has also been at the forefront in the development of data-driven discovery methods for analyzing global climate and ecosystem data.

 

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