C4.5: programs for machine learning
C4.5: programs for machine learning
Learning parse and translation decisions from examples with rich context
Learning parse and translation decisions from examples with rich context
Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text
Constraint Grammar: A Language-Independent System for Parsing Unrestricted Text
Serial combination of rules and statistics: a case study in Czech tagging
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Application of syntactic properties to three-level recognition of polish hand-written medical texts
Proceedings of the 2006 ACM symposium on Document engineering
Using part of speech n-grams for improving automatic speech recognition of polish
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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Stochastic approaches to tagging of Polish brought results far from being satisfactory However, successful combination of hand-written rules and a stochastic approach to Czech, as well, as some initial experiments in acquisition of tagging rules for Polish revealed potential capabilities of a rule based approach The goals are: to define a language of tagging constraints, to construct a set of reduction rules for Polish and to apply Machine Learning to extraction of tagging rules A language of functional tagging constraints called JOSKIPI is proposed An extension to the C4.5 algorithm based on introducing complex JOSKIPI operators into decision trees is presented Construction of a preliminary hand-written tagging rules for Polish is discussed Finally, the results of the comparison of different versions of the tagger are given.