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A Resource-Light Approach to Cross-Language
Information Retrieval AbstractThis paper aims at describing how the combination of light resources such as standard bilingual dictionaries and multilingual corpora can be formalized and exploited in the general and efficient framework of the Relevance Model (RM) approach to Cross-language Information Retrieval (CLIR). This combination of light resources is then compared with state-of-the-art CLIR methods and, particularly, those based on merging different Machine Translation systems and retrieval engines. It is shown experimentally that using an appropriate mix of resources extracted from standard dictionaries, general parallel corpora and (possibly) specialised comparable corpora in the RM framework allows to achieve performance at least equal to these current state-of-the-art methods.
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