Abstract
In this paper we study the problem of learning of Stochastic Context-Free Grammars by means of estimation algorithms. In these algorithms, which are based on a gradient descendent technique, the initial model play an important role. Here we explore the use of initial SCFG obtained from a treebank corpus. Experiments on the UPenn Treebank corpus are reported.
This work has been partially supported by the Spanish CICYT under contract (TIC2002/04103-C03-03)
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Linares, D., Sánchez, JA., Benedí, JM., Torres, F. (2003). Learning of Stochastic Context-Free Grammars by Means of Estimation Algorithms and Initial Treebank Grammars. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_47
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DOI: https://doi.org/10.1007/978-3-540-44871-6_47
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