Parameter Estimation for LDA-Frames

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Authors

MATERNA Jiří

Year of publication 2013
Type Article in Proceedings
Conference Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
MU Faculty or unit

Faculty of Informatics

Citation
Web http://www.aclweb.org/anthology/N/N13/
Field Informatics
Keywords LDA-Frames; semantic frames; valency frames; non-parametric methods
Description LDA-frames is an unsupervised approach for identifying semantic frames from semantically unlabeled text corpora, and seems to be a useful competitor for manually created databases of selectional preferences. The most limiting property of the algorithm is such that the number of frames and roles must be predefined. In this paper we present a modification of the LDA-frames algorithm allowing the number of frames and roles to be determined automatically, based on the character and size of training data.
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