Abstract
The unprecedented growth of electronic data and ever increasing user dependence on electronic data in today’s world suggests that data should be regarded as one of the most important assets of the users. Within the last few years Data Mining and Knowledge Discovery technology has established itself as a key technology for enterprises that wish to improve the quality of the results obtained from data analysis, decision support, and the automatic extraction of knowledge from data. The Data Mining Track focuses on the logical and physical design of knowledge discovery systems, particularly, on data classification and clustering, association rules, data mining techniques, data analysis and discovery, and data mining applications.
Similar content being viewed by others
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mohania, M. (2005). Data Mining Track Chair’s Message. In: Chakraborty, G. (eds) Distributed Computing and Internet Technology. ICDCIT 2005. Lecture Notes in Computer Science, vol 3816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11604655_58
Download citation
DOI: https://doi.org/10.1007/11604655_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30999-4
Online ISBN: 978-3-540-32429-4
eBook Packages: Computer ScienceComputer Science (R0)