Query term disambiguation for Web cross-language information retrieval using a search engine
IRAL '00 Proceedings of the fifth international workshop on on Information retrieval with Asian languages
Improving query translation for cross-language information retrieval using statistical models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Numerical Methods Using MATLAB
Numerical Methods Using MATLAB
Statistical cross-language information retrieval using n-best query translations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Cross-lingual relevance models
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Using Statistical Translation Models for Bilingual IR
CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
A maximum coherence model for dictionary-based cross-language information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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Query translation is the mainstream in cross-language information retrieval, but ambiguity must be resolved by methods based on dictionary translation. In this paper, we propose a progressive algorithm for disambiguation which is derived from another algorithm we propose called the max-sum model. The new algorithm take a strategy called weighted-average probability distribution to redistribute the probabilities. Moreover, the new algorithm can be computed in a more direct way by solving an equation system. All the resource our method requires is a bilingual dictionary and a monolingual corpus. Experiments show it outperforms four other methods.