— To enhance the generalization capacity of a distribution learning method, we propose to use a fuzzy Bayesian framework based on Bayes rules. The precision of the learning resul...
We propose a novel conception language for exploring the results retrieved by several internet search services (like search engines) that cluster retrieved documents. The goal is ...
Gloria Bordogna, Alessandro Campi, Giuseppe Psaila...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
This paper presents an iterative method for generative semantic clustering of related information elements in spatial hypertext documents. The goal is to automatically organize th...
Andruid Kerne, Eunyee Koh, Vikram Sundaram, J. Mic...