The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Abstract. Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies i...
Zhiyuan Yao, Annika H. Holmbom, Tomas Eklund, Barb...
Abstract. This paper centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering is applied to classified examples ...
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...
Clustering is crucial to many applications in pattern recognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most su...