Evaluating sense disambiguation across diverse parameter spaces
Natural Language Engineering
The role of domain information in Word Sense Disambiguation
Natural Language Engineering
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
HLT '91 Proceedings of the workshop on Speech and Natural Language
HLT '93 Proceedings of the workshop on Human Language Technology
Finding predominant word senses in untagged text
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Dependency-Based Construction of Semantic Space Models
Computational Linguistics
Text Categorization for Improved Priors of Word Meaning
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
On robustness and domain adaptation using SVD for word sense disambiguation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Supervised domain adaption for WSD
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Sussx: WSD using automatically acquired predominant senses
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval-2010 task 17: all-words word sense disambiguation on a specific domain
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
From predicting predominant senses to local context for word sense disambiguation
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
Knowledge-based WSD on specific domains: performing better than generic supervised WSD
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Classifying relations for biomedical named entity disambiguation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Knowledge-rich Word Sense Disambiguation rivaling supervised systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
All words domain adapted WSD: finding a middle ground between supervision and unsupervision
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
IIITH: Domain specific word sense disambiguation
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
HIT-CIR: An unsupervised WSD system based on domain most frequent sense estimation
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
CFILT: Resource conscious approaches for all-words domain specific WSD
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Proceedings of the 20th ACM international conference on Information and knowledge management
Disambiguation of medline abstracts using topic models
Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics
A quick tour of word sense disambiguation, induction and related approaches
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
Lexical acquisition for clinical text mining using distributional similarity
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
A new minimally-supervised framework for domain word sense disambiguation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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Distributions of the senses of words are often highly skewed. This fact is exploited by word sense disambiguation (WSD) systems which back off to the predominant sense of a word when contextual clues are not strong enough. The domain of a document has a strong influence on the sense distribution of words, but it is not feasible to produce large manually annotated corpora for every domain of interest. In this paper we describe the construction of three sense annotated corpora in different domains for a sample of English words. We apply an existing method for acquiring predominant sense information automatically from raw text, and for our sample demonstrate that (1) acquiring such information automatically from a mixed-domain corpus is more accurate than deriving it from SemCor, and (2) acquiring it automatically from text in the same domain as the target domain performs best by a large margin. We also show that for an all words WSD task this automatic method is best focussed on words that are salient to the domain, and on words with a different acquired predominant sense in that domain compared to that acquired from a balanced corpus.