A Comparative Study Between Possibilistic And Probabilistic Approaches For Query Translation Disambiguation

We propose in this paper a new hybrid possibilistic query translation disambiguation approach combining a probability-to-possibility transformation-based approach with a discriminative possibilistic one in order to take advantage of their strengths. The disambiguation process in this approach requires a bilingual lexicon and a parallel text corpus. Given a source query terms, the first step consists of selecting the existing noun phrases (NPs) and the remaining single terms which are not included in any NPs. We have translated these identified NPs as units through the probability-to-possibility transformation-based approach, as a mean to introduce further tolerance, using a language model and translation patterns. Then, the remaining single source query terms are translated via the discriminative possibilistic approach. We have modelled in this step the translation relevance of a given single source query term via two measures: the possible relevance excludes irrelevant translations, while the necessary relevance reinforces the translations not removed by the possibility. We have developed a set of experiments using the CLEF-2003 French-English CLIR test collection and the French-English parallel text corpus Europarl. The reported results highlight some statistically significant improvements of the hybrid possibilistic approach in the CLIR effectiveness using diverse evaluation metrics and scenarios for both long and short queries.