Paper: Generalizing Dependency Features for Opinion Mining

ACL ID P09-2079
Title Generalizing Dependency Features for Opinion Mining
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

We explore how features based on syntac- tic dependency relations can be utilized to improve performance on opinion mining. Using a transformation of dependency re- lation triples, we convert them into “com- posite back-off features” that generalize better than the regular lexicalized depen- dency relation features. Experiments com- paring our approach with several other ap- proaches that generalize dependency fea- tures or ngrams demonstrate the utility of composite back-off features.