Dependency Relation Triples Matching for Question Answering
依赖关系三元组匹配在问题回答中的应用

This paper presents a new method to compute the similarity between question and answer sentences, namely dependency relation triples matching. This method considers the information of question s interrogative part and non- interrogative part, and heuristic rules are used to expand question s relation triples to match metamorphosing answer sentences. Then, this similarity score is used as a new feature for answer ranking in open domain question answering (QA) track. The experiments show the new answer ranking method outperforms the common density-based approach by up to 8.2% in relative precision and 8% in mean reciprocal rank (MRR) evaluation.