| 我国知识产权研究领域的共词网络分析 |
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| 引用本文： | 蔡伟,王建冬,郑玉凤,王继民.我国知识产权研究领域的共词网络分析[J].图书情报工作,2013,57(10):116-121. |
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| 作者姓名： | 蔡伟 王建冬 郑玉凤 王继民 |
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| 作者单位： | 1. 北京市科技信息中心;
2. 国家信息中心信息化研究部;
3. 北京大学信息管理系 |
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| 基金项目： | 北京市科技计划项目"科学知识图谱方法在新兴产业发展态势分析中的应用研究" |
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| 摘 要： | 国内知识产权研究领域的关键词共现网络顶点度分布符合幂律分布特征,具有较高的聚类系数和较低的平均距离,符合复杂网路特征。通过G-N聚类分析,发现目前国内知识产权研究领域主要包括知识产权的数字化挑战、知识产权与技术创新等七大子领域。引入关键词的学科隶属度算法,对经济管理学、图书情报学和法学在知识产权领域的研究热点分布情况进行可视化分析,发现图书情报学在知识产权的数字化挑战及其应对方面的研究优势明显,进而建议图书情报学界加强跨学科合作,拓展学科覆盖面。
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| 关 键 词： | 知识产权 共词网络 G-N聚类算法 学科隶属度算法 |
| 收稿时间： | 2013-03-04 |
| 修稿时间： | 2013-04-23 |
Co-word Network Analysis on the Research Fields of Domestic Intellectual Property Research |
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| Cai Wei,Wang Jiandong,Zheng Yufeng,Wang Jimin.Co-word Network Analysis on the Research Fields of Domestic Intellectual Property Research[J].Library and Information Service,2013,57(10):116-121. |
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| Authors: | Cai Wei Wang Jiandong Zheng Yufeng Wang Jimin |
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| Institution: | 1. Beijing Sci-tech Information Center, Beijing 100044;
2. Informatization Research Department, SIC, Beijing 100045;
3. Department of Information Management, Peking University, Beijing 100871 |
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| Abstract: | The keywords co-occurrence network of domestic intellectual property research conforms to the characteristics of complex networks, with high clustering coefficient, low average distance and the vertex degree distribution obeys the rule of the power-law distribution. The main content of the intellectual property research includes seven parts, such as the digital challenge and technological innovation of intellectual property. Information Science's obvious advantage in the digital challenge of intellectual property was found through the visualized analysis about the hot research topic in Economic Management、Information Science、Law by introducing the algorithm of disciplinary attribution. The researchers of Information Science were suggested to strengthen the interdisciplinary collaboration and expand the subject coverage. |
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| Keywords: | intellectual property co-word network G-N clustering algorithm disciplinary attribution algorithm |
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