1 research outputs found
A Probabilistic Translation Method for Dictionary-based Cross-lingual Information Retrieval in Agglutinative Languages
Translation ambiguity, out of vocabulary words and missing some translations
in bilingual dictionaries make dictionary-based Cross-language Information
Retrieval (CLIR) a challenging task. Moreover, in agglutinative languages which
do not have reliable stemmers, missing various lexical formations in bilingual
dictionaries degrades CLIR performance. This paper aims to introduce a
probabilistic translation model to solve the ambiguity problem, and also to
provide most likely formations of a dictionary candidate. We propose Minimum
Edit Support Candidates (MESC) method that exploits a monolingual corpus and a
bilingual dictionary to translate users' native language queries to documents'
language. Our experiments show that the proposed method outperforms
state-of-the-art dictionary-based English-Persian CLIR.Comment: The 3rd conference of Computational Linguistic, Sharif University of
Technology, November 201