Authors:
Oussama Ben Khiroun
1
;
Bilel Elayeb
2
and
Narjès Bellamine Ben Saoud
3
Affiliations:
1
Manouba University and Sousse University, Tunisia
;
2
Manouba University and Emirates College of Technology, Tunisia
;
3
Manouba University, Tunisia
Keyword(s):
Cross-Language Information Retrieval, Possibility Theory, Parallel Corpus, Co-occurrence Graph, Query Translation Disambiguation, Query Expansion.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Representation and Reasoning
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
We propose in this paper a combined method for Cross-Language Information Retrieval (CLIR) using statistical
and lexical resources. On the one hand, we extracted a bilingual French to English dictionary from aligned
texts of the Europarl collection. On the other hand, we built a co-occurrence graph structure and used the
BabelNet lexical network to process the disambiguation of translation candidates for ambiguous words. We
compared our new possibilistic approach with circuit-based one and studied the impact of query expansion by
adopting the pseudo-relevance feedback (PRF) technique. Our experiments are performed using the standard
CLEF-2003 collection. The results show the positive impact of PRF on the query translation process. Besides,
the possibilistic approach using the co-occurrence graph outperforms the overall circuit-based runs.