An automatic method for generating sense tagged corpora
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Natural Language Engineering
Word-sense disambiguation using decomposable models
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Mining the Web for bilingual text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
An unsupervised method for word sense tagging using parallel corpora
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Building a sense tagged corpus with open mind word expert
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Word sense disambiguation using sense examples automatically acquired from a second language
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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We present a novel approach for automatically acquiring English topic signatures. Given a particular concept, or word sense, a topic signature is a set of words that tend to co-occur with it. Topic signatures can be useful in a number of Natural Language Processing (NLP) applications, such as Word Sense Disambiguation (WSD) and Text Summarisation. Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web. We evaluated the topic signatures on a WSD task, where we trained a second-order vector cooccurrence algorithm on standard WSD datasets, with promising results.