文章摘要
雷鸣,孟菊园,杨雪梅,汪雪锋.基于SAO 结构的知识演化路径分析:以医疗机器人领域为例[J].情报工程,2018,4(6):051-061
基于SAO 结构的知识演化路径分析:以医疗机器人领域为例
Knowledge Evolutionary Path Analysis Based on SAO Structure: Case Study of Medical Robots
  
DOI:10.3772/j.issn.2095-915X.2018.06.005
中文关键词: 知识演化路径  SAO 结构  主路径分析  医疗机器人
英文关键词: Knowledge evolutionary path  SAO structure  main path analysis  medical robots
基金项目:知识演化路径;SAO 结构;主路径分析;医疗机器人
作者单位
雷鸣 1. 兰州交通大学交通运输学院 
孟菊园 2. 北京理工大学管理与经济学院 
杨雪梅 2. 北京理工大学管理与经济学院 
汪雪锋 2. 北京理工大学管理与经济学院 
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中文摘要:
      知识演化路径分析可以识别出知识演化过程中的关键信息,在识别知识创新趋势和把握知识发展脉络方面具有重要意义。当前知识演化路径的研究主要从主题词的相关关系入手,忽略了主题词间的语义关系和知识发展过程中的演化关系。利用主路径分析中的关键路径(Key-Route)方法,论文将SAO 结构及其关系引入到演化路径分析中,系统构建了基于SAO 结构的知识演化路径绘制流程,并在医疗机器人领域进行了探索性研究。研究表明基于SAO 结构的知识演化路径可以呈现更加丰富的语义信息,帮助科研人员快速识别知识演化的潜在原因及其发展方向。实证表明该方法具有可行性和有效性。
英文摘要:
      Knowledge evolutionary path analysis contributes to identify the critical information in the process of evolution, which is significant to recognize the knowledge innovation trend and grasp the knowledge venation. Current methods of tracing knowledge evolutionary path ignore the semantic relationships between these keywords and the evolutive relationships between different topics because they focus on the correlation between keywords. Based on the ke y-route methods of main path analysis,this paper constructed drawing process of knowledge evolutionary path based on SAO structure and their relationships, and then applied this systematical method to medical robots field. The results illustrated that knowledge evolutionary path based on SAO structure can present abundant semantic information, which is beneficial to identify potential causes and development direction of knowledge evolution effectively for researchers. This case study demonstrates that the feasibility and effectiveness of this method.
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