Improving data driven wordclass tagging by system combination

Improving data driven wordclass tagging by system combination (1998)

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by Hans Van Halteren , Jakub Zavrel , Walter Daelemans

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@INPROCEEDINGS{Halteren98improvingdata,
    author = {Hans Van Halteren and Jakub Zavrel and Walter Daelemans},
    title = {Improving data driven wordclass tagging by system combination},
    booktitle = {},
    year = {1998},
    pages = {491--497},
    publisher = {}
}

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Abstract

In this paper we examine how the differences in modelling between different data driven systems performing the same NLP task can be exploited to yield a higher accuracy than the best indi-vidua | system. We do this by means of an ex-periment involving the task of morpho-syntactic wordclass tagging. Four well-known tagger gen-erators (Hidden Markov Model, Memory-Based, Transformation Rules and Maximum Entropy)

Citations

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