Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
HLT '93 Proceedings of the workshop on Human Language Technology
Word independent context pair classification model for word sense disambiguation
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Vector-Based Unsupervised Word Sense Disambiguation for Large Number of Contexts
TSD '09 Proceedings of the 12th International Conference on Text, Speech and Dialogue
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UBC-AS: a graph based unsupervised system for induction and classification
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UPV-SI: word sense induction using self term expansion
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Extracting glosses to disambiguate word senses
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Co-occurrence cluster features for lexical substitutions in context
TextGraphs-5 Proceedings of the 2010 Workshop on Graph-based Methods for Natural Language Processing
Inducing word senses to improve web search result clustering
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Clustering web search results with maximum spanning trees
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
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
Evaluation of clustering algorithms for word sense disambiguation
International Journal of Data Analysis Techniques and Strategies
An evaluation of graded sense disambiguation using word sense induction
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
Creating a system for lexical substitutions from scratch using crowdsourcing
Language Resources and Evaluation
Evaluating Word Sense Induction and Disambiguation Methods
Language Resources and Evaluation
| Hi-index | 0.00 |
Véronis (2004) has recently proposed an innovative unsupervised algorithm for word sense disambiguation based on small-world graphs called HyperLex. This paper explores two sides of the algorithm. First, we extend Véronis' work by optimizing the free parameters (on a set of words which is different to the target set). Second, given that the empirical comparison among unsupervised systems (and with respect to supervised systems) is seldom made, we used hand-tagged corpora to map the induced senses to a standard lexicon (WordNet) and a publicly available gold standard (Senseval 3 English Lexical Sample). Our results for nouns show that thanks to the optimization of parameters and the mapping method, HyperLex obtains results close to supervised systems using the same kind of bag-of-words features. Given the information loss inherent in any mapping step and the fact that the parameters were tuned for another set of words, these are very interesting results.