In this paper, we propose a document clustering method that strives to achieve: (1) a high accuracy of document clustering, and (2) the capability of estimating the number of clus...
We consider a semi-supervised setting for domain adaptation where only unlabeled data is available for the target domain. One way to tackle this problem is to train a generative m...
Abstract-Similarity searching often reduces to finding the k nearest neighbors to a query object. Finding the k nearest neighbors is achieved by applying either a depth-first or a ...
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
In this paper, we apply AntClust, an ant based clustering algorithm, to the Web usage-mining problem. We define a Web session as a weighted multi-modal vector and we propose an ad...
Gilles Venturini, Nicolas Labroche, Nicolas Monmar...