A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
Most previously proposed mining methods on data streams make an unrealistic assumption that "labelled" data stream is readily available and can be mined at anytime. Howe...
Multivariate statistical analysis is an important data analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analy...
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Distributed data mining (DDM) is the semi-automatic pattern extraction of distributed data sources. The next generation of the data mining studies will be distributed data mining ...
Ezendu Ifeanyi Ariwa, Mohamed B. Senousy, Mohamed ...
We have developed a sales support system for door-todoor sales of cosmetics based on a skin-image grading system called Skin-CRM (Skin Customer Relationship Management). Our Skin-...
Understanding rework, the causes of rework, and the relationship between issues, decisions and the associated actions, is crucial in minimizing the fundamental industrial problems ...
Caroline Chibelushi, Bernadette Sharp, Andy Salter
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
We describe an implementation of an algorithm for enumerating all maximal frequent sets using irredundant dualization, which is an improved version of that of Gunopulos et al. The...