Several previous systems allow users to interactively explore a large input graph through cuts of a superimposed hierarchy. This hierarchy is often created using clustering algorit...
: We initiate the study of local, sublinear time algorithms for finding vertices with extreme topological properties -- such as high degree or clustering coefficient -- in large so...
We present an approach to improving the precision of an initial document ranking wherein we utilize cluster information within a graph-based framework. The main idea is to perform...
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
Abstract. We present a novel algorithm called DBSC, which finds subspace clusters in numerical datasets based on the concept of ”dependency”. This algorithm employs a depth-...