Chapman & Hall/CRC
Data Mining and Knowledge Discovery Series
PUBLISHED TITLES
SERIES EDITOR
Vipin Kumar
University of Minnesota
Department of Computer Science and Engineering
Minneapolis, Minnesota, U.S.A.
AIMS AND SCOPE
This series aims to capture new developments and applications in data mining and knowledge
discovery, while summarizing the computational tools and techniques useful in data analysis.
This series encourages the integration of mathematical, statistical, and computational meth-
ods and techniques through the publication of a broad range of textbooks, reference works,
and handbooks. The inclusion of concrete examples and applications is highly encouraged. The
scope of the series includes, but is not limited to, titles in the areas of data mining and knowledge
discovery methods and applications, modeling, algorithms, theory and foundations, data and
knowledge visualization, data mining systems and tools, and privacy and security issues.
ACCELERATING DISCOVERY: MINING UNSTRUCTURED INFORMATION FOR
HYPOTHESIS GENERATION
Scott Spangler
ADVANCES IN MACHINE LEARNING AND DATA MINING FOR ASTRONOMY
Michael J. Way, Jerey D. Scargle, Kamal M. Ali, and Ashok N. Srivastava
BIOLOGICAL DATA MINING
Jake Y. Chen and Stefano Lonardi
COMPUTATIONAL BUSINESS ANALYTICS
Subrata Das
COMPUTATIONAL INTELLIGENT DATA ANALYSIS FOR SUSTAINABLE
DEVELOPMENT
Ting Yu, Nitesh V. Chawla, and Simeon Simo
COMPUTATIONAL METHODS OF FEATURE SELECTION
Huan Liu and Hiroshi Motoda
CONSTRAINED CLUSTERING: ADVANCES IN ALGORITHMS, THEORY,
AND APPLICATIONS
Sugato Basu, Ian Davidson, and Kiri L. Wagsta
CONTRAST DATA MINING: CONCEPTS, ALGORITHMS, AND APPLICATIONS
Guozhu Dong and James Bailey
DATA CLASSIFICATION: ALGORITHMS AND APPLICATIONS
Charu C. Aggarawal
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