G. Escudero, L. M`arquez, and G. Rigau. Naive Bayes and Exemplar-Based Approaches to Word Sense Disambiguation Revisited. In To appear in Proceedings of the 14th European Conference on Artificial Intelligence, ECAI, Berlin, Germany, 2000. Home/Search Document Details and Download
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Machine Learning and Natural Language Processing - Marquez (2000) (1 citation) (Correct)
....back off estimates. We can find the NB algorithm (either the basic version or other variations and hybrids) applied to the following NLP disambiguation tasks: Context sensitive spelling correction [88, 89] PoS tagging [194, 189] PP attachment disambiguation [52] Word sense disambiguation [86, 150, 156, 112, 73] and Text Categorization [117, 190, 119, 142, 196] Recently, Lau, Rosenfeld and Roukos [110, 187] have proposed a new approach for combining statistical evidence from different sources, that is based on the Maximum Entropy Principle (ME) This work was originated within the speech recognition ....
....training set. 9 [55, 14, 56, 15] PoS tagging [61, 60, 90] PP attachment disambiguation [246] shallow parsing [227] and smoothing of probability estimates [245] The work of other authors include applications to partial parsing (chunking) and context sensitive parsing [210, 7, 33] WSD [159, 157, 84, 73], text categorization [183, 238, 237, 239] semantic interpretation [38] machine translation [100] and lexical acquisition by analogy [76, 75] 2.2.6 Inductive Logic Programming (ILP) This is a discipline devoted to the inductive learning of Prolog programs from examples. The most relevant ....
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G. Escudero, L. M`arquez, and G. Rigau. Naive Bayes and Exemplar-Based Approaches to Word Sense Disambiguation Revisited. In To appear in Proceedings of the 14th European Conference on Artificial Intelligence, ECAI, Berlin, Germany, 2000.
Exploring automatic word sense disambiguation with decision.. - Agirre, Martínez (2000) (3 citations) (Correct)
....skewed words, where we can expect better performance than average. 4.8 Overall DSO: state of the art results In order to compare decision lists with other state of the art algorithms we tagged all 191 words in the DSO corpus. The results in (Ng, 1997) only tag two subsets of all the data, but (Escudero et al. 2000a) implement both Ng s example based (EB) approach and a Naive Bayes (NB) system and test it on all 191 words. The same test set is also used in (Escudero et al. 2000b) which presents a boosting approach to word sense disambiguation. The features they use are similar to ours, but not exactly. The ....
....of the art algorithms we tagged all 191 words in the DSO corpus. The results in (Ng, 1997) only tag two subsets of all the data, but (Escudero et al. 2000a) implement both Ng s example based (EB) approach and a Naive Bayes (NB) system and test it on all 191 words. The same test set is also used in (Escudero et al. 2000b) which presents a boosting approach to word sense disambiguation. The features they use are similar to ours, but not exactly. The precision obtained, summarized on Table 7 show that decision lists provide state ofthe art performance. Decision list attained 0.99 coverage. 5 Cross tagging: hand ....
Escudero, G., L. Mrquez and G. Rigau. Naive Bayes and Exemplar-Based approaches to Word Sense Disambiguation Revisited. Proceedings of the 14th European Conference on Artificial Intelligence, ECAI 2000. 2000.
An Empirical Study of the Domain Dependence of.. - Escudero, Màrquez, Rigau (2000) Self-citation (Escudero Rigau) (Correct)
.... Many standard ML algorithms for supervised learning have been applied, such as: Decision Lists (Yarowsky, 1994; Agirre and Martinez, 2000) Neural Networks (Towell and Voorhees, 1998) Bayesian learning (Bruce and Wiebe, 1999) Exemplar Based learning (Ng, 1997a; Fujii et al. 1998) Boosting (Escudero et al. 2000a) etc. Unfortunately, there have been very few direct comparisons between alternative methods for WSD. In general, supervised learning presumes that the training examples are somehow re ective of the task that will be performed by the trainee on other data. Consequently, the performance of ....
....example. In the experiments explained in section 4, the EB algorithm is run several times using di erent number of nearest neighbours (1, 3, 3 Although the use of MVDM metric (Cost and Salzberg, 1993) could lead to better results, current implementations have prohivitive computational overheads (Escudero et al. 2000b) 5, 7, 10, 15, 20 and 25) and the results corresponding to the best choice are reported 4 . Exemplar based learning is said to be the best option for WSD (Ng, 1997a) Other authors (Daelemans et al. 1999) point out that exemplar based methods tend to be superior in language learning ....
[Article contains additional citation context not shown here]
G. Escudero, L. Marquez, and G. Rigau. 2000b. Naive Bayes and Exemplar-Based Approaches to Word Sense Disambiguation Revisited. In To appear in Proceedings of the 14th European Conference on Articial Intelligence, ECAI.
On the Portability and Tuning of Supervised Word Sense.. - Escudero, Marquez, Rigau (2000) (2 citations) Self-citation (Escudero Rigau) (Correct)
....pseudo words. Many standard ML algorithms for supervised learning have been applied to WSD, including: Decision Lists (Yarowsky, 1994) Neural Networks (Towell and Voorhees, 1998) Bayesian learning (Bruce and Wiebe, 1999) Exemplar based learning (Ng, 1997a; Fujii et al. 1998) and Boosting (Escudero et al. 2000a) Further, in (Mooney, 1996) some of the previously cited methods are compared, jointly with Decision Trees and Rule Induction algorithms, on a very restricted domain. The performance of supervised ML based systems is usually calculated by testing the algorithm on a separate part of the set ....
....obtain from Internet arbitrarily large samples of word senses (Leacock et al. 1998; Mihalcea and Moldovan, 1999) 3. The use of unsupervised EM like algorithms for estimating the statistical model parameters (Pedersen and Bruce, 1998) 4. The application of efficient and accurate ML algorithms (Escudero et al. 2000a) and attribute representations (Escudero et al. 2000b) in order to deal with real size WSD problems. Solving the problem of knowledge acquisition is crucial for making the unsupervised WSD approach viable. It is our belief that the referred work, and especially second and fourth lines, ....
[Article contains additional citation context not shown here]
G. Escudero, L. M`arquez, and G. Rigau. 2000b. Naive Bayes and Exemplar-Based Approaches to Word Sense Disambiguation Revisited. In To appear in Proceedings of the 14th European Conference on Artificial Intelligence, ECAI, Berlin, Germany.
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