— Clustering is grouping of patterns according to similarity or distance in different perspectives. Various data representations, similarity measurements and organization manners...
A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
Abstract. The paper presents a clustering method which can be applied to populated ontologies for discovering interesting groupings of resources therein. The method exploits a simp...
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters...
This paper discusses a new type of semi-supervised document clustering that uses partial supervision to partition a large set of documents. Most clustering methods organizes docum...
Abstract. With the rapid development of on-line information services, information technologies for on-line information processing have been receiving much attention recently. Clust...
Clustering can be used to identify groups of similar solutions in Multimodal Optimisation. However, a poor clustering quality reduces the benefit of this application. The vast maj...
It is a key activity in CBD to identify high-quality components which have high cohesion and low coupling. However, component clustering is carried out in manual fashion by develop...
Document clustering has been used as a core technique in managing vast amount of data and providing needed information. In on-line environments, generally new information gains mo...