2006 TwoGraphBasedAlgsForWSD
- (Agirre et al., 2006) ⇒ Eneko Agirre, David Martínez, Oier Lopez de Lacalle, and Aitor Soroa. (2006). “Two Graph-based Algorithms for State-of-the-Art WSD.” In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2006).
Subject Headings: Unsupervised WSD Algorithm, Senseval-3.
Notes
Cited By
- ~37 http://scholar.google.com/scholar?q=%22Two+Graph-based+Algorithms+for+State-of-the-Art+WSD.%22+2006
Quotes
Abstract
This paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora. Our main contribution is the optimization of the free parameters of those algorithms and its evaluation against publicly available gold standards. We present a thorough evaluation comprising supervised and unsupervised modes, and both lexical-sample and all-words tasks. The results show that, in spite of the information loss inherent to mapping the induced senses to the gold-standard, the optimization of parameters based on a small sample of nouns carries over to all nouns, performing close to supervised systems in the lexical sample task and yielding the second-best WSD systems for the Senseval-3 all-words task.
References
- Eneko Agirre, O. Lopez de Lacalle, and D. Martinez. (2005). Exploring feature spaces with svd and unlabeled data for word sense disambiguation. In: Proceedings of RANLP.
- Eneko Agirre, O. Lopez de Lacalle, D. Martinez, and A. Soroa. (2006). Evaluating and optimizing the parameters of an unsupervised graph-based wsd algorithm. In: Proceedings of the NAACL Texgraphs workshop.
- S. Brin, and L. Page. (1998). The anatomy of a largescale hypertextual web search engine. Computer Networks and ISDN Systems, 30(1-7).
- D. Alan Cruse, (2000). Polysemy: Theoretical and Computational Approaches, chapter Aspects of the Microstructure of Word Meanings, pages 3151. OUP.
- G Erkan and D. R. Radev. (2004). Lexrank: Graphbased centrality as salience in text summarization. Journal of Artificial Intelligence Research (JAIR).
- C. Fellbaum. (1998). WordNet: An Electronic Lexical Database. MIT Press.
- Jon Kleinberg. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM, 46(5):604632.
- Rada Mihalcea and P Tarau. (2004). Textrank: Bringing order into texts. In: Proceedings of EMNLP2004.
- Rada Mihalcea, T. Chklovski, and A. Kilgarriff. (2004). The senseval-3 english lexical sample task. In
- Rada Mihalcea and P. Edmonds, editors, Senseval-3 proccedings, pages 2528. ACL, July.
- Rada Mihalcea. (2005). Unsupervised large-vocabulary word sense disambiguation with graph-based algorithms for sequence data labeling. In: Proceedings of EMNLP2005.
- G. A. Miller, C. Leacock, R. Tengi, and R.Bunker. (1993). A semantic concordance. In: Proceedings of the ARPA HLT workshop.
- Roberto Navigli and Paola Velardi. (2005). Structural semantic interconnections: a knowledge-based approach to word sense disambiguation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 7(27):10631074, June.
- C. Niu,W. Li, Rohini K Srihari, and H. Li. (2005). Word independent context pair classification model for word sense disambiguation. In: Proceedings of CoNLL-2005.
- Patrick Pantel and Dekang Lin. (2002). Discovering word senses from text. In: Proceedings of KDD02.
- A. Purandare and T. Pedersen. (2004). Word sense discrimination by clustering contexts in vector and similarity spaces. In: Proceedings of CoNLL-2004, pages 4148.
- Hinrich Schütze. (1998). Automatic word sense discrimination. Computational Linguistics, 24(1):97123.
- B. Snyder and M. Palmer. (2004). The english all-words task. In: Proceedings of SENSEVAL.
- J. Véronis. (2004). Hyperlex: lexical cartography for information retrieval. Computer Speech & Language, 18(3):223252.
- Y Zhao and G Karypis. (2005). Hierarchical clustering algorithms for document datasets. Data Mining,