Research on the Application of Hyponymy in the Enrollment Robot
Yu Xincong1,2, Li Honglian1, Lv Xueqiang2
1 School of Information Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China;
2 Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China
[Objective] This paper aims at increasing the accuracy, and improving the satisfaction of question answer system. [Context] In the field of Natural Language Processing, question answering system has become an important research point, but the accuracy of system is low at present. How to improve the satisfaction of the system becomes the burning question. [Methods] This paper analyzes the source code of ALICE for modification by using the Chinese word segmentation. Based on the analysis of its internal reasoning, this paper puts forward a recommend method. [Results] Integrate the domain Ontology into ALICE robot, then analyze the user question, extract key words. Finally, search the Ontology and then give the recommends. [Conclusions] Experiments show that after introducing Ontology of recommended results, customer satisfaction is increased greatly.
余昕聪, 李红莲, 吕学强. 本体上下位关系在招生问答机器人中的应用研究[J]. 现代图书情报技术, 2015, 31(12): 65-71.
Yu Xincong, Li Honglian, Lv Xueqiang. Research on the Application of Hyponymy in the Enrollment Robot. New Technology of Library and Information Service, 2015, 31(12): 65-71.
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