Implicit Feature Detection via a Constrained Topic Model and SVM

Implicit feature detection, also known as implicit feature identification, is an essential aspect of feature-specific opinion mining but previous works have often ignored it. We think, based on the explicit sentences, several Support Vector Machine (SVM) classifiers can be established to do this task. Nevertheless, we believe it is possible to do better by using a constrained topic model instead of traditional attribute selection methods. Experiments show that this method outperforms the traditional attribute selection methods by a large margin and the detection task can be completed better.