This paper presents a new approach designed to reduce the computational load of the existing clustering algorithms by trimming down the documents size using fingerprinting methods...
An overview of cluster analysis techniques from a data mining point of view is given. This is done by a strict separation of the questions of various similarity and distance measur...
Abstract. Algorithms or target functions for graph clustering rarely admit quality guarantees or optimal results in general. Based on properties of minimum-cut trees, a clustering ...
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
In spatial clustering, the scale of spatial data is usually very large. Spatial clustering algorithms need high performance, good scalability, and are able to deal with noise and ...