Translating collocations for bilingual lexicons: a statistical approach
Computational Linguistics
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Computational Linguistics
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IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Bilingual lexicon generation using non-aligned signatures
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Revisiting context-based projection methods for term-translation spotting in comparable corpora
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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Proceedings of the 20th ACM international conference on Information and knowledge management
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The explosion of multilingual opinion data has made essential the need for automatic tools to analyze and understand people's opinions in multilingual reviews. In cross-language opinion mining, bilingual opinion lexicon plays a central role. Most of the bilingual lexicon extraction methods are based on EM algorithm. However, these methods are faced with two major problems: high complexity and unsatisfying precision. In this paper, we propose a novel approach to extract bilingual opinion lexicon using collocation alignment, where a collocation is a combination of a feature word and an opinion word. There are tight association between feature words and opinion words, which can be helpful to reduce the computation space and alignment errors. Experimental results demonstrate that our solution is effective and competitive.