Knowledge-Oriented Answer Extraction in Chinese Question Answering System for E-Learning

The research work on question answering (QA) system is a very important field in e-learning. The factoid QA system has developed rapidly in recent years and it is basically a solved problem. However, how to answer questions beyond factoid is still a challengeable task. In this paper, we propose an approach for knowledge-oriented answer extraction beyond factoid. Furthermore, we focus on the answer classification step in the task of answer extraction. Experimental results show that our method is viable.