A Possibilistic Query Translation Approach for Cross-Language Information Retrieval

Ben Romdhane Wiem (1) , Bilel Elayeb (1, 2) , Ibrahim Bounhas (3) , Fabrice Evrard (4) , Narjes Bellamine-Bensaoud (1)

1 RIADI - Laboratoire de recherche en Génie Logiciel, Applications distribuées, Systèmes décisionnels et Imagerie intelligente [Manouba]
2 Emirates College of Technology
3 Laboratory of Computer Science for Industrial Systems - LISI (Manouba,Tunisie)
4 IRIT-LILaC - Logique, Interaction, Langue et Calcul

In this paper, we explore several statistical methods to find solutions to the problem of query translation ambiguity. Indeed, we propose and compare a new possibilistic approach for query translation derived from a probabilistic one, by applying a classical probability-possibility transformation of probability distributions, which introduces a certain tolerance in the selection of word translations. Finally, the best words are selected based on a similarity measure. The experiments are performed on CLEF-2003 French-English CLIR collection, which allowed us to test the effectiveness of the possibilistic approach.

Mots clés: Cross-language information retrieval (CLIR); Query translation; Possibilistic approach

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]; Informatique et langage [cs.CL]

Ben Romdhane Wiem, Bilel Elayeb, Ibrahim Bounhas, Fabrice Evrard, Narjes Bellamine-Bensaoud. A Possibilistic Query Translation Approach for Cross-Language Information Retrieval. 9th International Conference on Intelligent Computing (ICIC 2013), Jul 2013, Nanning, China. pp. 73-82. ⟨hal-01228727⟩