The use of cache memories and symmetric Kullback-Leibler distances is proposed for topic classification and topic-shift detection. Experiments with a large corpus of articles from the French newspaper "Le Monde show tangible advantages when different models are combined with a suitable strategy. Experimental results show that different strategies for topic shift detection have to be used depend...

A computational model of the origins of syllables systems is presented : a society of robotic agents endowed with realistic motor, perceptual and cognitive apparati is shown to build from scratch shared syllable systems in a decentralized manner. Furthermo re, these systems share many structural properties with those of human languages. Résumé Un modèle opérationel de l'origine des systèmes syl...

Le besoin d’intégrer et d’analyser des grandes masses est présent dans de nombreux domaines d’applications. Le problème de l’alignement d’ontologies/schémas dont le résultat est un ensemble de correspondances entre différentes représentations du monde réel, est au centre du processus d’intégration des données. En effet, l’intégration de données est motivée par la forte hétérogénéité des données...

This paper describes the combination of a stochastic language model and a formal grammar modelled such as a unification grammar. The stochastic model is trained over 42 million words extracted from Le monde newspaper. The stochastic model is based on smoothed 3-gram and 3-class. The 3-class model is represented by a Markov chain made up of four states. Several experiments have been done to stat...

We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between...

A new statistical method for Language Modeling and spoken document classification is proposed. It is based on a mixture of topic dependent probabilities. Each topic dependent probability is in turn a mixture of n-gram probabilities and the probability of Kullback-Lieber (KL) distances between key-word unigrams and distribution obtained from the content of a cache memory. Experimental result on ...

The correct attachment of prepositional phrases (PPs) is a central disambiguation problem when parsing natural languages. This paper compares the baseline situation for French as exemplified in the Le Monde treebank with earlier findings for English, German and Swedish. We perform uniform treebank queries and show that the noun attachment rate for French prepositions is strongly influenced by t...