Generalizing dependency features for opinion mining
Published 1 January 2009Open access
Mahesh Joshi, Carolyn Penstein Rosé
Citations179
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TL;DR
Using a transformation of dependency relation triples, features based on syntactic dependency relations can be utilized to improve performance on opinion mining by being converted into composite back-off features that generalize better than the regular lexicalized dependency relation features.
Abstract
We explore how features based on syntactic dependency relations can be utilized to improve performance on opinion mining. Using a transformation of dependency relation triples, we convert them into "composite back-off features" that generalize better than the regular lexicalized dependency relation features. Experiments comparing our approach with several other approaches that generalize dependency features or ngrams demonstrate the utility of composite back-off features.
Keywords
Computer Science
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