A Probabilistic Translation Method for Dictionary-based Cross-lingual Information Retrieval in Agglutinative Languages
نویسندگان
چکیده
Translation ambiguity, out of vocabulary words and missing some translations in bilingual dictionaries make dictionary-based Crosslanguage 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. 1
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ورودعنوان ژورنال:
- CoRR
دوره abs/1411.1006 شماره
صفحات -
تاریخ انتشار 2014