
Data Mining
Next Generation Challenges and Future Directions
AAAI Press
Published on 19. November 2004
Book
Paperback/Softback
528 pages
978-0-262-61203-6 (ISBN)
Description
A state-of-the-art survey of recent advances in data mining or knowledge discovery.
Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recognition, databases, and high performance computing, data mining extracts useful information from the large data sets now available to industry and science. This collection surveys the most recent advances in the field and charts directions for future research. The first part looks at pervasive, distributed, and stream data mining, discussing topics that include distributed data mining algorithms for new application areas, several aspects of next-generation data mining systems and applications, and detection of recurrent patterns in digital media. The second part considers data mining, counter-terrorism, and privacy concerns, examining such topics as biosurveillance, marshalling evidence through data mining, and link discovery. The third part looks at scientific data mining; topics include mining temporally-varying phenomena, data sets using graphs, and spatial data mining. The last part considers web, semantics, and data mining, examining advances in text mining algorithms and software, semantic webs, and other subjects.
Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recognition, databases, and high performance computing, data mining extracts useful information from the large data sets now available to industry and science. This collection surveys the most recent advances in the field and charts directions for future research. The first part looks at pervasive, distributed, and stream data mining, discussing topics that include distributed data mining algorithms for new application areas, several aspects of next-generation data mining systems and applications, and detection of recurrent patterns in digital media. The second part considers data mining, counter-terrorism, and privacy concerns, examining such topics as biosurveillance, marshalling evidence through data mining, and link discovery. The third part looks at scientific data mining; topics include mining temporally-varying phenomena, data sets using graphs, and spatial data mining. The last part considers web, semantics, and data mining, examining advances in text mining algorithms and software, semantic webs, and other subjects.
More details
Series
Language
English
Place of publication
Cambridge
United States
Publishing group
MIT Press Ltd
Target group
Professional and scholarly
Interest Age: From 18 to 99 years
Product notice
Paperback (trade)
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 32 mm
Weight
794 gr
ISBN-13
978-0-262-61203-6 (9780262612036)
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Schweitzer Classification
Persons
Hillol Kargupta is Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. Anupama Joshi is the Executive Director and Cofounder of the National Farm to School Network, a project of Tides Center (formerly based at the Urban & Environmental Policy Institute at Occidental College). Krishnamoorthy Sivakumar is Assistant Professor in the School of Electrical Engineering and Computer Science at Washington State University. Yelena Yesha is Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County.