The new generation of search engines based on natural language processing

Current trends in natural language processing and information retrieval are briefly analysed to show their impace on the search engine market. Powerset and Hakia are highlighted as the main agents of this change

Semantic Grounding Strategies for Tagbased Recommender Systems

Recommender systems usually operate on similarities between recommended items or users. Tag based recommender systems utilize similarities on tags. The tags are however mostly free user entered phrases. Therefore, similarities computed without their semantic groundings might lead to less relevant recommendations. In this paper, we study a semantic grounding used for tag similarity calculus. We show a comprehensive analysis of semantic grounding given by 20 ontologies from different domains. The study besides other things reveals that currently available OWL ontologies are very narrow and the percentage of the similarity expansions is rather small. WordNet scores slightly better as it is broader but not much as it does not support several semantic relationships. Furthermore, the study reveals that even with such number of expansions, the recommendations change considerably.Comment: 13 pages, 5 figure

Exploiting association rules and ontology for semantic document indexing

International audienceThis paper describes a novel approach for document indexing based on the discovery of contextual semantic relations between concepts. The concepts are first extracted from WordNet ontology. Then we propose to extend and to use the association rules technique in order to discover conditional relations between concepts. Finally, concepts and related contextual relations are organized into a conditional graph

A descriptive study about Wordnet (MCR) and linguistics synsets

Este artigo apresenta o trabalho realizado para aplicar a WordNet MCR ao domínio linguístico e discute as situações problemáticas geradas pela estrutura WordNet e pelas características inerentes ao domínio. Foi empregado o enfoque descritivo para explicar como a manutenção da estrutura original da WordNet pode afetar as extensões de um domínio específico. Nossos resultados mostram que, para poder ampliar os synsets de domínios específicos, é inevitável uma reorganização estrutural

Analyse de l'ambiguïté des requêtes utilisateurs par catégorisation thématique.

International audienceDans cet article, nous cherchons à identifier la nature de l'ambiguïté des requêtes utilisateurs issues d'un moteur de recherche dédié à l'actualité, 2424actu.fr, en utilisant une tâche de catégorisation. Dans un premier temps, nous verrons les différentes formes de l'ambiguïté des requêtes déjà décrites dans les travaux de TAL. Nous confrontons la vision lexicographique de l'ambiguïté à celle décrite par les techniques de classification appliquées à la recherche d'information. Dans un deuxième temps, nous appliquons une méthode de catégorisation thématique afin d'explorer l'ambiguïté des requêtes, celle-ci nous permet de conduire une analyse sémantique de ces requêtes, en intégrant la dimension temporelle propre au contexte des news. Nous proposons une typologie des phénomènes d'ambiguïté basée sur notre analyse sémantique. Enfin, nous comparons l'exploration par catégorisation à une ressource comme Wikipédia, montrant concrètement les divergences des deux approches

Corpus-Based Techniques for Word Sense Disambiguation

The need for robust and easily extensible systems for word sense disambiguation coupled with successes in training systems for a variety of tasks using large on-line corpora has led to extensive research into corpus-based statistical approaches to this problem. Promising results have been achieved by vector space representations of context, clustering combined with a semantic knowledge base, and decision lists based on collocational relations. We evaluate these techniques with respect to three important criteria: how their definition of context affects their ability to incorporate different types of disambiguating information, how they define similarity among senses, and how easily they can generalize to new senses. The strengths and weaknesses of these systems provide guidance for future systems which must capture and model a variety of disambiguating information, both syntactic and semantic