Abstract
We report on a set of experiments in text mining, specifically, finding semantic patterns given only a few keywords. The experiments employ the Counter-training framework for discovery of semantic knowledge from raw text in a weakly supervised fashion. The experiments indicate that the framework is suitable for efficient acquisition of semantic word classes and collocation patterns, which may be used for Information Extraction.
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Yangarber, R. (2005). Mining the Semantics of Text Via Counter-Training. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_63
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DOI: https://doi.org/10.1007/11595014_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30737-2
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