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New Technology of Library and Information Service  2015, Vol. 31 Issue (12): 65-71    DOI: 10.11925/infotech.1003-3513.2015.12.10
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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
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[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.

Received: 03 June 2015      Published: 06 April 2016
:  TP393  

Cite this article:

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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[1] 冯志伟. 自然语言问答系统的发展与现状[J]. 外国语: 上海外国语大学学报, 2012, 35(6): 2-16. (Feng Zhiwei. Question-Answer System of Natural Language: Past and Present [J]. Journal of Foreign Languages, 2013, 35(6): 2-16.)
[2] 王树西. 问答系统: 核心技术、发展趋势[J]. 计算机工程与应用, 2005, 41(18): 1-3. (Wang Shuxi. Question Answering System: Core Technology, Application [J]. Computer Engineering and Applications, 2005, 41 (18): 1-3.)
[3] Zheng Z. AnswerBus Question Answering System [C]. In: Proceedings of the 2nd International Conference on Human Language Technology Research, 2002: 399-404.
[4] The START Natural Language Question Answering System [DB/OL]. [2006-12-16].
[5] 冯德虎. 基于ALICE的研究生招生咨询智能聊天机器人研究与实现[D]. 成都: 西南交通大学, 2013. (Feng Dehu. Research and Implementation of the Graduate Admissions Counseling Intelligent Chat Robot Based on ALICE [D]. Chengdu: Southwest Jiaotong University, 2013.)
[6] 周永梅. 基于本体的自动问答系统[D]. 镇江: 江苏科技大学, 2011. (Zhou Yongmei. Research on Automatic Question Answering System Based on Ontology [D]. Zhenjiang: Jiangsu University of Science and Technology, 2011.)
[7] 陈小宾. 领域本体及其在移动问答中的应用研究[D]. 大连: 大连理工大学, 2009. (Chen Xiaobin. Research on Domain Ontology and the Application in Mobile Question Answering [D]. Dalian: Dalian University of Technology, 2009.)
[8] Zhang H, Kishore R, Sharman R, et al. Agile Integration Modeling Language (AIML): A Conceptual Modeling Grammar for Agile Integrative Business Information Systems [J]. Decision Support Systems, 2007, 44(1): 266-284.
[9] 刘汉兴, 林旭东, 田绪红. 基于本体的自动答疑系统的研究与实现[J]. 计算机应用, 2010, 30(2): 415-418. (Liu Hanxing, Lin Xudong, Tian Xuhong. Research and Implementation of Automatic Question Answering System Based on Ontology [J]. Computer Applications, 2010, 30 (2): 415-418.)
[10] 刘宇松. 本体构建方法和开发工具研究[J]. 现代情报, 2009, 29(9): 17-24. (Liu Yusong. Research on Ontology Construction Methods and Development Tools [J]. Modern Intelligence, 2009, 29 (9): 17-24.)
[11] Jena 2: A Semantic Web Framework for Java [CP]. [2006-05-04].
[12] 刘里, 曾庆田. 自动问答系统研究综述[J]. 山东科技大学学报: 自然科学版, 2007, 26(4): 73-76. (Liu Li, Zeng Qingtian. Overview of Automatic Question Answering System [J]. Journal of Shandong University of Science and Technology: Natural Science Edition, 2007, 26 (4): 73-76.)

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