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Published in:
2015 | OriginalPaper | Chapter
Research on Open Domain Question Answering System
Authors : Zhonglin Ye, Zheng Jia, Yan Yang, Junfu Huang, Hongfeng Yin
Published in: Natural Language Processing and Chinese Computing
Publisher: Springer International Publishing
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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 provided 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.