Data Mining, or Knowledge Discovery, has become an indispensable technology for business 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 set 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 discusses 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 examines such topics as bio-surveillance, marshalling evidence through data mining, and link discovery. The third focuses at scientific data mining; and the 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.

The book serves as a supplementary text for the students of Information Technology.

It should also be of interest to the professionals of knowledge management.