W. Daelemans, J. Zavrel, Berck P., and Gillis S. submitted. Memory-Based Part of Speech Tagging. Tilburg University.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... semantic grammars and building prolog parsers 113 (Zelle and Mooney, 1994; Zelle and Mooney, 1993) the use of conceptual clustering algorithms for rel ative pronoun resolution (Cardie, 1992a; Cardie 1992b) and the use of case based learning techniques for lexical tagging tasks (Cardie, 1993a; Daelemans et al. submitted) In theory, both sta tistical and machine learning techniques can significantly reduce the knowledge engineering effort for building large scale NLP systems: they offer an automatic means for acquiring robust heuris tics for a host of lexical and structural disam biguation tasks. It is ....

....to adapt it to the current problemsolving situation. Case based learning algorithms have been used in NLP for context sensitive pars ing (Simmons and Yu, 1992) for text categoriza tion (Riloffand Lehnert, 1994) for lexical tagging tasks like part of speech tagging and semantic feature tagging (Daelemans et al. submitted, Cardie, 1994, Cardie, 1993a) for semantic interpretation (e.g. concept extraction (Cardie, 1994, Cardie, 1993a) and for a number of low level language acquisition tasks, including stress acquisition (Daelemans et al. 1994) and graphemeto phoneme conversion (Bosch and Daelemans, 1993) In ....

W. Daelemans, J. Zavrel, Berck P., and Gillis S. submitted. Memory-Based Part of Speech Tagging. Tilburg University.

....it turned out that no positive value for the feature [flap Sigma] occurred in any of the words in the dialects examined. We therefore experimented with weighing each feature by information gain, a number expressing the average entropy reduction a feature represents when known (Quinlan, 1993; Daelemans et al. 1996). To calculate this we need a base figure for database entropy: H(D) Gamma X i p i log 2 p i If we have n different vectors for all the dialects, then 1 i n. p i is the probability of vector i, estimated by its frequency divided by jDj, which is the total number of vectors in all ....

Daelemans, Walter, Jakub Zavrel, Peter Berck, and Steven Gillis. 1996. Memory-based part of speech tagging. In Gert Durieux, Walter Daelemans, and Steven Gillis, editors, Proc. of CLIN '95. Antwerpen, pages 185--202.

.... semantic grammars and building prolog parsers (Zelle and Mooney, 1994; Zelle and Mooney, 1993) the use of conceptual clustering algorithms for relative pronoun resolution (Cardie, 1992a; Cardie 1992b) and the use of case based learning techniques for lexical tagging tasks (Cardie, 1993a; Daelemans et al. submitted) In theory, both statistical and machine learning techniques can significantly reduce the knowledge engineering effort for building large scale NLP systems: they offer an automatic means for acquiring robust heuristics for a host of lexical and structural disambiguation tasks. It is well known ....

....adapt it to the current problemsolving situation. Case based learning algorithms have been used in NLP for context sensitive parsing (Simmons and Yu, 1992) for text categoriza tion (Riloff and Lehnert, 1994) for lexical tagging tasks like part of speech tagging and semantic feature tagging (Daelemans et al. submitted, Cardie, 1994, Cardie, 1993a) for semantic interpretation (e.g. concept extraction (Cardie, 1994, Cardie, 1993a) and for a number of low level language acquisition tasks, including stress acquisition (Daelemans et al. 1994) and graphemeto phoneme conversion (Bosch and Daelemans, 1993) In ....

W. Daelemans, J. Zavrel, Berck P., and Gillis S. submitted. Memory-Based Part of Speech Tagging. Tilburg University.

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