Towards a New Possibilistic Query Translation Tool for Cross-Language Information Retrieval.

TitleTowards a New Possibilistic Query Translation Tool for Cross-Language Information Retrieval.
Publication TypeJournal Article
Year of Publication2018
AuthorsElayeb, B, Ben Romdhane, W, Ben Saoud, NBellamine
JournalMultimedia Tools and Applications, Springer.
Volume77
Issue2
Pagination2423–2465
Abstract

Approaches of query translation in Cross-Language Information Retrieval (CLIR) have frequently used dictionaries which suffer from translation ambiguity. Besides, a word-by-word query translation is not sufficient. In this paper, we propose, evaluate and compare a new possibilistic approach for query translation in order to improve the previous dictionary-based ones. This approach uses a probability-to-possibility transformation as a mean to introduce further tolerance in query translation process. Firstly, we identify noun phrases (NPs) in the source query and translate them as units using translation patterns and a language model. Secondly, source query terms which are not included in any selected NPs are translated word-by-word using our new possibilistic approach of single word translation. Indeed, we take into account all query words and their translations when we choose the suitable translation of a given word. We start from the idea that the correct suitable translations of query terms have a tendency to co-occur in the target language documents unlike unsuitable ones. Finally, to increase the coverage of the bilingual dictionary, additional words and their translations are automatically generated from a parallel bilingual corpus. We tested our approach using the French-English parallel text corpus Europarl and the CLEF-2003 French-English CLIR test collection. The reported experiments showed the performance of the probability-to-possibility transformation-based approach compared to the probabilistic one and to some state-of-the-art CLIR tools.