An IR approach for translating new words from nonparallel, comparable texts
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Learning bilingual collocations by word-level sorting
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
A bootstrapping method for extracting bilingual text pairs
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Using the web as a bilingual dictionary
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Effect of cross-language IR in bilingual lexicon acquisition from comparable corpora
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Focused web crawling in the acquisition of comparable corpora
Information Retrieval
Using comparable corpora to improve the effectiveness of cross-language information retrieval
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
Creating a Persian-English comparable corpus
CLEF'10 Proceedings of the 2010 international conference on Multilingual and multimodal information access evaluation: cross-language evaluation forum
Topic based creation of a persian-english comparable corpus
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
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For the purpose of overcoming resource scarcity bottleneck in corpus-based translation knowledge acquisition research, this paper takes an approach of semi-automatically acquiring domain specific translation knowledge from the collection of bilingual news articles on WWW news sites. This paper presents results of applying standard co-occurrence frequency based techniques of estimating bilingual term correspondences from parallel corpora to relevant article pairs automatically collected from WWW news sites. The experimental evaluation results are very encouraging and it is proved that many useful bilingual term correspondences can be efficiently discovered with little human intervention from relevant article pairs on WWW news sites.