Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data...
Feature extraction and knowledge discovery from a large amount of image data such as remote sensing images have become highly required recent years. In this study, a framework for ...
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
This paper surveys some genetic-fuzzy data mining techniques for mining both membership functions and fuzzy association rules. The motivation from crisp mining to fuzzy mining wil...