A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
Abstract. Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the nu...
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
The concept of older adults contributing to society in a meaningful way has been termed `active ageing'. We present applications of data mining techniques on the active agein...
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...