Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
Abstract. The goal of this article is to introduce a collaborative clustering approach to the domain of ubiquitous knowledge discovery. This clustering approach is suitable in peer...
Abstract. Scientists’ ability to generate and collect massive-scale datasets is increasing. As a result, constraints in data analysis capability rather than limitations in the av...
YongChul Kwon, Dylan Nunley, Jeffrey P. Gardner, M...
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...