Abstract:

In recent years, the number of studies concerning Cross-Language Information Retrieval (CLIR) has grown rapidly, due to the increased availability of linguistic resources for research. Cross-Language Information Retrieval consists of providing a query in one language and searching document collections in one or more languages. Therefore, a translation form is required. In the present paper, we focus on query translation, disambiguation and expansion in order to improve the effectiveness of information retrieval through various combinations of these methods. First, we are interested to find retrieval methods that are capable of performing across languages and which do not rely on scarce resources such as parallel corpora. Bilingual Machine Readable-Dictionaries (MRDs), more prevalent than parallel texts, appear to be a good alternative. However, simple translations tend to be ambiguous and yield poor results. A combination that includes a statistical approach for a disambiguation can significantly reduce errors associated with polysemy1 in dictionary translation. In addition, automatic query expansion, which has been known to be among the most important methods in overcoming the word mismatch problem in information retrieval, is also considered. As an assumption to reduce the effect of ambiguity and errors that a dictionary-based method would cause, a combined statistical disambiguation method is performed both prior to and after translation. Although, the proposed information retrieval system is general across languages in information retrieval, we conducted experiments and evaluations concerning French-English information retrieval.