Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
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
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Structural Semantic Interconnections: A Knowledge-Based Approach to Word Sense Disambiguation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Finding predominant word senses in untagged text
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Ensemble methods for unsupervised WSD
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
WordNet::Similarity: measuring the relatedness of concepts
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
SemEval-2007 task 07: coarse-grained English all-words task
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
KU: word sense disambiguation by substitution
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
NUS-PT: exploiting parallel texts for word sense disambiguation in the English all-words tasks
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UPV-WSD: combining different WSD methods by means of fuzzy Borda voting
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Extended gloss overlaps as a measure of semantic relatedness
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Using measures of semantic relatedness for word sense disambiguation
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Using web selectors for the disambiguation of all words
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Acquiring applicable common sense knowledge from the Web
UMSLLS '09 Proceedings of the Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics
SemEval-2010 task 17: All-words word sense disambiguation on a specific domain
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
UCF-WS: Domain word sense disambiguation using web selectors
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Penn: using word similarities to better estimate sentence similarity
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
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This paper presents a method of acquiring knowledge from the Web for noun sense disambiguation. Words, called selectors, are acquired which take the place of an instance of a target word in its local context. The selectors serve for the system to essentially learn the areas or concepts of WordNet that the sense of a target word should be a part of. The correct sense is chosen based on a combination of the strength given from similarity and relatedness measures over WordNet and the probability of a selector occurring within the local context. Our method is evaluated using the coarse-grained all-words task from SemEval 2007. Experiments reveal that pathbased similarity measures perform just as well as information content similarity measures within our system. Overall, the results show our system is out-performed only by systems utilizing training data or substantially more annotated data.