The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Two graph-based algorithms for state-of-the-art WSD
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
| Hi-index | 0.00 |
This paper is an outcome of ongoing research and presents an unsupervised method for automatic word sense induction (WSI) and disambiguation (WSD). The induction algorithm is based on modeling the cooccurrences of two or more words using hypergraphs. WSI takes place by detecting high-density components in the cooccurrence hypergraphs. WSD assigns to each induced cluster a score equal to the sum of weights of its hyperedges found in the local context of the target word. Our system participates in SemEval-2007 word sense induction and discrimination task.