A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Quantifying the utility of parallel corpora
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Comparing cross-language query expansion techniques by degrading translation resources
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
The Effect of Bilingual Term List Size on Dictionary-Based Cross-Language Information Retrieval
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 4 - Volume 4
Character N-Gram Tokenization for European Language Text Retrieval
Information Retrieval
Char_align: a program for aligning parallel texts at the character level
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Cross-lingual information retrieval using hidden Markov models
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Translation techniques in cross-language information retrieval
ACM Computing Surveys (CSUR)
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JHU/APL continued to explore the use of knowledge-light methods for multilingual retrieval during the CLEF 2004 evaluation. We relied on the language-neutral techniques of character n-gram tokenization, pre-translation query expansion, statistical translation using aligned parallel corpora, fusion from disparate retrievals, and reliance on language similarity when resources are scarce. We participated in the monolingual and bilingual evaluations. Our results support the claims that n-gram based retrieval is highly effective; that fusion of multiple retrievals is helpful in bilingual retrieval; and, that reliance on language similarity in lieu of translation can outperform a high performing system using abundant translation resources and a less similar query language.