An instance-based approach for pinpointing answers in chinese question answering

In this paper, we propose an instance-based approach for pinpointing answers in Chinese question answering (QA). We take the view that, for a particular class, the strategy of answering new questions can be learned from the already solved ones. To confirm the feasibility of this new approach, we use question answer pairs (QA pair) as our learning instances and maximum entropy model (MEM) as a machine learning (ML) technique. The experiment conducted on the class-LOC_COUNTRY and OBJ_LANGUAGE achieves good performance