Word sense disambiguation in information retrieval revisited
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
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
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Using a semantic concordance for sense identification
HLT '94 Proceedings of the workshop on Human Language Technology
An empirical evaluation of knowledge sources and learning algorithms for word sense disambiguation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
SenseLearner: word sense disambiguation for all words in unrestricted text
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
LIBLINEAR: A Library for Large Linear Classification
The Journal of Machine Learning Research
Scaling up word sense disambiguation via parallel texts
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
SemEval-2007 task 17: English lexical sample, SRL and all words
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
English tasks: all-words and verb lexical sample
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Pattern learning and active feature selection for word sense disambiguation
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
The Johns Hopkins SENSEVAL2 system descriptions
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Predicting the uncertainty of sentiment adjectives in indirect answers
Proceedings of the 20th ACM international conference on Information and knowledge management
Does word sense disambiguation improve information retrieval?
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
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
Multilingual WSD with just a few lines of code: the BabelNet API
ACL '12 Proceedings of the ACL 2012 System Demonstrations
Word sense disambiguation improves information retrieval
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Evaluating measures of semantic similarity and relatedness to disambiguate terms in biomedical text
Journal of Biomedical Informatics
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Word sense disambiguation (WSD) systems based on supervised learning achieved the best performance in SensEval and SemEval workshops. However, there are few publicly available open source WSD systems. This limits the use of WSD in other applications, especially for researchers whose research interests are not in WSD. In this paper, we present IMS, a supervised English all-words WSD system. The flexible framework of IMS allows users to integrate different preprocessing tools, additional features, and different classifiers. By default, we use linear support vector machines as the classifier with multiple knowledge-based features. In our implementation, IMS achieves state-of-the-art results on several SensEval and SemEval tasks.