7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
Recently, a new generation of adaptive process management technology has emerged, which enables dynamic changes of composite services and process models respectively. This, in tur...
To obtain correlated and complementary information contained in text mining and bibliometrics, hybrid clustering to incorporate textual content and citation information has become...
Bart De Moor, Frizo A. L. Janssens, Shi Yu, Wolfga...
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...