An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Using syntactic dependency as local context to resolve word sense ambiguity
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Using a semantic concordance for sense identification
HLT '94 Proceedings of the workshop on Human Language Technology
Domain-specific sense distributions and predominant sense acquisition
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Acquiring knowledge from the web to be used as selectors for noun sense disambiguation
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Using web selectors for the disambiguation of all words
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
SemEval-2010 task 17: All-words word sense disambiguation on a specific domain
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
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This paper studies the application of the Web Selectors word sense disambiguation system on a specific domain. The system was primarily applied without any domain tuning, but the incorporation of domain predominant sense information was explored. Results indicated that the system performs relatively the same with domain predominant sense information as without, scoring well above a random baseline, but still 5 percentage points below results of using the first sense.