Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
This paper proposes a new method for comparing clusterings both partitionally and geometrically. Our approach is motivated by the following observation: the vast majority of previ...
Michael H. Coen, M. Hidayath Ansari, Nathanael Fil...
Granular Computing (GrC), a knowledge-oriented computing which covers the theory of fuzzy information granularity, rough set theory, the theory of quotient space and interval comp...