Probabilistic topic models are unsupervised generative models which model document
content as a two-step generation process, that is, documents are observed as mixtures of …

The idea of automatic extraction of important information from text documents comes from
the time of first steps in the natural language processing. Its importance rapidly grows with …

In this article, we present a new algorithm for clustering a bilingual collection of comparable
news items in groups of specific topics. Our hypothesis is that named entities (NE s) are …

With the rich data on the web, a documents clustering task for monolingual documents is
insufficient in order to produce an efficient information retrieval system. A Multilingual …