Paper: Implicit Feature Detection via a Constrained Topic Model and SVM

ACL ID D13-1092
Title Implicit Feature Detection via a Constrained Topic Model and SVM
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Implicit feature detection, also known as im- plicit feature identification, is an essential as- pect of feature-specific opinion mining but previous works have often ignored it. We think, based on the explicit sentences, sever- al Support Vector Machine (SVM) classifier- s can be established to do this task. Never- theless, we believe it is possible to do bet- ter by using a constrained topic model instead of traditional attribute selection methods. Ex- periments show that this method outperforms the traditional attribute selection methods by a large margin and the detection task can be completed better.