A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Multilingual Information Retrieval Based on Parallel Texts from the Web
CLEF '00 Revised Papers from the Workshop of Cross-Language Evaluation Forum on Cross-Language Information Retrieval and Evaluation
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Empirical studies on the impact of lexical resources on CLIR performance
Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
Confidence estimation for translation prediction
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
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Query translation in Cross Language Information Retrieval (CLIR) can be performed using multiple resources. Previous attempts to combine different translation resources use simple methods such as linear combination. Unfortunately, these approaches are insufficient to combine different types of resources such as bilingual dictionaries and statistical translation models. In this paper, we use confidence measures for this combination for the purpose of English-Arabic CLIR. Confidence measure is used to adjust the original scores of translations and to create a weight of the same nature for translations with different resources. We tested this technique on two test CLIR collections from TREC and obtained encouraging improvements compared to the results of linear combination.