JAIST: Combining multiple features for Answer Selection in Community Question Answering

摘要

In this paper, we describe our system for SemEval-2015 Task 3: Answer Selection in Community Question Answering. In this task, the systems are required to identify the good or potentially good answers from the answer thread in Community Question Answering collections. Our system combines 16 features belong to 5 groups to predict answer quality. Our final model achieves the best result in sub-task A for English, both in accuracy and F1-score.