In this paper we present our technique for finding semantically similar clusters within web documents obtained from a set of queries retrieved from the Google search engine. This ...
We argue that when objects are characterized by many attributes, clustering them on the basis of a random subset of these attributes can capture information on the unobserved attr...
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
Phrase has been considered as a more informative feature term for improving the effectiveness of document clustering. In this paper, we propose a phrase-based document similarity t...
We proposed and implemented a novel clustering algorithm called LAIR2, which has constant running time average for on-the-fly Scatter/Gather browsing [4]. Our experiments showed ...