Lexical ambiguity and information retrieval
ACM Transactions on Information Systems (TOIS)
Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The impact on retrieval effectiveness of skewed frequency distributions
ACM Transactions on Information Systems (TOIS)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Information Retrieval
Word sense disambiguation in information retrieval revisited
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Homonymy and polysemy in information retrieval
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
Information retrieval using word senses: root sense tagging approach
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
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
Meaningful clustering of senses helps boost word sense disambiguation performance
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
SemEval-2010 task 2: cross-lingual lexical substitution
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Graph connectivity measures for unsupervised word sense disambiguation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The topology of synonymy and homonymy networks
CACLA '07 Proceedings of the Workshop on Cognitive Aspects of Computational Language Acquisition
Investigations on word senses and word usages
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Measuring similarity of word meaning in context with lexical substitutes and translations
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
Ontology-based distinction between polysemy and homonymy
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
An experimental study on syntactic and semantic annotations in text retrieval
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
ACM Transactions on Speech and Language Processing (TSLP)
Creating a system for lexical substitutions from scratch using crowdsourcing
Language Resources and Evaluation
Latent word context model for information retrieval
Information Retrieval
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Recent studies into Web retrieval have shown that word sense disambiguation can increase retrieval effectiveness. However, it remains unclear as to the minimum disambiguation accuracy required and the granularity with which one must define word sense in order to maximize these benefits. This study answers these questions using a simulation of the effects of ambiguity on information retrieval. It goes beyond previous studies by differentiating between homonymy and polysemy. Results show that retrieval is more sensitive to polysemy than homonymy and that, when resolving polysemy, accuracy as low as 55% can potentially lead to increased performance.