Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Clustering is the process of locating patterns in large data sets. It is an active research area that provides value to scientific as well as business applications. Practical clust...
Document clustering has been used for better document retrieval, document browsing, and text mining. In this paper, we investigate if biomedical ontology MeSH improves the cluster...