SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Introduction to the special issue on word sense disambiguation: the state of the art
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
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach
ACL '96 Proceedings of the 34th 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
Instance based learning with automatic feature selection applied to word sense disambiguation
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
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: Algorithms and Applications (Text, Speech and Language Technology)
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
SemEval-2007 task 07: coarse-grained English all-words task
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
LCC-WSD: system description for English coarse grained all words task at SemEval 2007
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Knowledge-rich Word Sense Disambiguation rivaling supervised systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
SemEval-2010 task 17: All-words word sense disambiguation on a specific domain
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
KCDC: Word sense induction by using grammatical dependencies and sentence phrase structure
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
TreeMatch: A fully unsupervised WSD system using dependency knowledge on a specific domain
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Contextual modeling for meeting translation using unsupervised word sense disambiguation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Artificial Intelligence Review
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Word sense disambiguation is the process of determining which sense of a word is used in a given context. Due to its importance in understanding semantics of natural languages, word sense disambiguation has been extensively studied in Computational Linguistics. However, existing methods either are brittle and narrowly focus on specific topics or words, or provide only mediocre performance in real-world settings. Broad coverage and disambiguation quality are critical for a word sense disambiguation system. In this paper we present a fully unsupervised word sense disambiguation method that requires only a dictionary and unannotated text as input. Such an automatic approach overcomes the problem of brittleness suffered in many existing methods and makes broad-coverage word sense disambiguation feasible in practice. We evaluated our approach using SemEval 2007 Task 7 (Coarse-grained English All-words Task), and our system significantly outperformed the best unsupervised system participating in SemEval 2007 and achieved the performance approaching top-performing supervised systems. Although our method was only tested with coarse-grained sense disambiguation, it can be directly applied to fine-grained sense disambiguation.