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2015
Springer

Combining Pattern-Based and Distributional Similarity for Graph-Based Noun Categorization

4 years 2 months ago
Combining Pattern-Based and Distributional Similarity for Graph-Based Noun Categorization
Abstract. We examine the combination of pattern-based and distributional similarity for the induction of semantic categories. Pattern-based methods are precise and sparse while distributional methods have a higher recall. Given these particular properties we use the prediction of distributional methods as a back-off to pattern-based similarity. Since our pattern-based approach is embedded into a semi-supervised graph clustering algorithm, we also examine how distributional information is best added to that classifier. Our experiments are carried out on 5 different food categorization tasks.
Michael Wiegand, Benjamin Roth, Dietrich Klakow
Added 15 Apr 2016
Updated 15 Apr 2016
Type Journal
Year 2015
Where NLDB
Authors Michael Wiegand, Benjamin Roth, Dietrich Klakow
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