Data mining is “the data-driven discovery and modeling of hidden patterns in large volumes of data.” Data mining differs from retrospective technologies because it produces models that capture and represent hidden patterns in the data. Space images have inspired researchers to study the intrinsic use of information gathering and information delivery. Remote sensing is one of the major applications and can have an impact on the next millennium. Data mining is the discovery of patterns, associations, anomalies, and statistically significant structures in data. It is a multi-disciplinary field, borrowing and enhancing ideas from diverse areas such as statistics, signal and image processing, image understanding, mathematical optimization, computer vision, and pattern recognition. It is the process of non-trivial extraction of implicit, previously unknown and potentially useful information from voluminous data. Advances in various fields including DNA sequencing, bioinformatics, ecommerce, fraud detection, knowledge management, remote sensing images, GIS, digital cartography, stock investment and prediction analysis, and real-time decision making have fueled it. Scientists in general, especially those working in the signal and image processing areas have now realized that they are ill-equipped to handle the overwhelming amounts of data emanating from a host of sources.
Data preprocessing, classic data mining techniques, model validation, advanced data mining techniques - fuzzy data mining, adaptive model estimation and fusion of signal data, distributed data mining and sensor networks, data mining in complex domains, web log mining, web content mining, visual data mining, spatial data mining, signal processing for mining information and filtering algorithms for time related data.
Submission Guidelines: Prospective authors should submit their responses to the web submission system at, http://www.cspl.umd.edu/spm/, according to the following timetable:
|White paper due:||March 1, 2003|
|Invitation notification:||March 15, 2003|
|Manuscript due:||July 1, 2003|
|Acceptance Notification:||December 1, 2003|
|Final Manuscript due:||January 15, 2003|
|Publication date:||February, 2004|
|S. S. Iyengar
Roy Paul Daniels Professor of Computer Science and Chairman.
Department of Computer Science
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Supercomputer Education and Research Center
Indian Institute of Science
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