W. Daelemans, T. Weijters, and A. van den Bosch. Empirical Learning of Natural Language Processing Tasks. Lecture Notes in Artificial Intelligence, number 1224. Springer-- Verlag, Berlin, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... permits the use and adaptation of general purpose machine learning algorithms for classification which are well known and widely studied methods , with the aim of providing general frameworks in which many disambiguation problems could be addressed simultaneously by homogeneous techniques [19, 31, 59, 188]. Some concrete publication statistics clearly illustrate the extent of the revolution in natural language research. As an example, a full 63.5 of the papers in the Proceedings of the Annual Meeting of the Association for Computational Linguistics and 47.7 of the papers in the journal ....

W. Daelemans, T. Weijters, and A. van den Bosch. Empirical Learning of Natural Language Processing Tasks. Lecture Notes in Artificial Intelligence, number 1224. Springer-- Verlag, Berlin, 1997.

....irrelevant to the language itself. This disadvantage has been the main source of criticism against the purely statistical approaches. The optimism about the marriage of ML and NLP stems from the observation that most NLP problems can be viewed as classification problems (Magerman, 1995; Daelemans, 1997). Empirical learning is fundamentally a classification paradigm and, as stated in (Daelemans, 1997) the point is to redefine linguistic tasks as classification tasks. In general, linguistic problems fall into two types of classification: a) Disambiguation, i.e. determine the correct category ....

....against the purely statistical approaches. The optimism about the marriage of ML and NLP stems from the observation that most NLP problems can be viewed as classification problems (Magerman, 1995; Daelemans, 1997) Empirical learning is fundamentally a classification paradigm and, as stated in (Daelemans, 1997), the point is to redefine linguistic tasks as classification tasks. In general, linguistic problems fall into two types of classification: a) Disambiguation, i.e. determine the correct category from a set of possible categories and (b) Segmentation, i.e. determine the correct boundary of a ....

Daelemans, W., Van den Bosch, A. and Weijters, A. (1997) Empirical Learning of Natural Language Processing Tasks. In W. Daelemans, A. Van den Bosch, and A. Weijters (eds.) Workshop Notes of the ECML/Mlnet Workshop on Empirical Learning of Natural Language Processing Tasks, Prague, pp.1-10.

.... Not Forget: Full Memory in Memory Based Learning of Word Pronunciation Antal van den Bosch and Walter Daelemans Tilburg University, ILK P.O. Box 90153, NL 5000 LE Tilburg The Netherlands fantalb,walterg kub.nl Abstract Memory based learning, keeping full memory of learning material, appears a viable approach to learning nlp tasks, and is often superior in generalisation accuracy to eager learning approaches that abstract from learning ....

Daelemans, W., A. Van den Bosch, and A. Weijters. 1997a. Empirical learning of natural language processing tasks. Lecture Notes in Artificial Intelligence, , number 1224, pages 337--344.

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Daelemans W., van den Bosch A. and Weijters T. Empirical Learning of Natural Language Processing Tasks. In W. Daelemans , A. van den Bosch and T. Weijters, editors, Workshop Notes of the ECM/MLnet Workshop on Empirical Learning of Natural Processing Tasks, April 26, 1997.

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