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作 者:关鹏 王曰芬[2] 曹嘉君[2] GUAN Peng;WANG Yue-fen;CAO Jia-jun(Institute of Applied Mathematics,Chaohu University,Hefei 238000,China;School of Economics and Management,Nanjing University of Science & Technology,Nanjing 210094,China)
机构地区:[1]巢湖学院应用数学学院,安徽合肥238000 [2]南京理工大学经济管理学院,江苏南京210094
出 处:《情报科学》2018年第9期3-8,共6页Information Science
基 金:国家自然科学基金(71373124)
摘 要:【目的/意义】当前,对学科研究前沿的挖掘和探测成为学科知识创新服务的重要支撑。本文从整合主题的视角出发,提出了学科知识网络构建与演化分析的框架,通过该框架实现学科研究前沿的挖掘和探测。【方法/过程】整合主题的学科知识网络构建与演化分析框架主要包括三个部分。一是,基于主题挖掘与主题语义关联计算相结合的视角,提出了整合主题的学科知识网络构建流程;二是,基于复杂网络结构分析理论提出了整合主题的网络结构演化分析方法,以挖掘和探测前沿主题;三是,基于复杂网络演化建模与多agent系统仿真建模方法,提出了整合主题的学科知识网络演化建模框架,通过演化建模探索学科知识结构的演化机理。【结果/结论】以上整合主题的学科知识网络构建流程和演化分析、演化建模框架,形成了"主题挖掘→网络构建→结构演化→仿真建模"的研究新思路,为学科知识创新服务提供了新的方法与工具。【Purpose/significance】At present, mining and exploration of research fronts has become an important support for academic knowledge innovation services. From the perspective of integrating topics, this paper proposes a framework for the construction and evolution analysis of discipline knowledge networks. Through this framework, research fronts of discipline could be found. 【Method/process】This paper puts forward the framework from three aspects. First, it proposes the constructing process of discipline knowledge network based on integrating topics, through topic extraction and topic semantic association calculation. Second, it puts forward evaluation analysis method of network structure, by complexity network structure analysis theory. Third, it puts forward frame of network evaluation modeling, based on complexity network evaluation modeling and multi-agent system modeling. 【Result/conclusion】Through the above steps, the paper puts forward a research idea, which follows the line of"topic mining"to"network construction"to"structure evaluation"to"simulation modeling". This frame work can support new methods and tools for knowledge service oriented to discipline knowledge innovation.
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