Research on Open Domain Question Answering System [chapter]

Zhonglin Ye, Zheng Jia, Yan Yang, Junfu Huang, Hongfeng Yin
2015 Lecture Notes in Computer Science  
Aiming at open domain question answering system evaluation task in the fourth CCF Natural Language Processing and Chinese Computing Conference (NLPCC2015), a solution of automatic question answering which can answer natural language questions is proposed. Firstly, SPE (Subject Predicate Extraction) algorithm is presented to find answers from the knowledge base, and then WKE (Web Knowledge Extraction) algorithm is used to extract answers from search engine query result. Experimental data
more » ... in the evaluation task includes the knowledge base and questions in natural language. The evaluation result shows that MRR is 0.5670, accuracy is 0.5700, and average F1 is 0.5240, and indicates the proposed method is feasible in open domain question answering system.
doi:10.1007/978-3-319-25207-0_49 fatcat:rlwmo5j35neb7loosldx6w76ay