【目的】分析国内外专利网络研究进展,梳理研究现状、发现研究问题和研判研究趋势。【文献范围】分别以"Patent Network"和"专利网络"为主题在Web of Science核心集和CNKI核心期刊库中检索,通过去重、去除不相关文...【目的】分析国内外专利网络研究进展,梳理研究现状、发现研究问题和研判研究趋势。【文献范围】分别以"Patent Network"和"专利网络"为主题在Web of Science核心集和CNKI核心期刊库中检索,通过去重、去除不相关文献后,共检索到英文论文465篇,中文论文196篇,分析其中代表性论文106篇。【方法】首先,利用团渗透重叠社区发现算法对"专利网络"关键词共现网络进行主题挖掘,分析中英文热点研究主题;其次,对热点研究主题下的高被引论文进行述评。【结果】综合现有研究,专利网络构建方法主要有合作关系、引用关系、技术转移关系、技术相似关系等,主流研究方法有社会网络分析、复杂网络和文本挖掘等。【局限】仅对热点研究领域的高被引代表性论文进行分析,未能覆盖全部研究主题和文献。【结论】专利网络研究尚未形成系统性的理论和方法体系,新兴研究方法的应用仍处于探索阶段。专利网络分析需向中观层面深入,网络演化机制、模型和仿真实验研究还需进一步加强。专利网络语义化分析倾向越来越明显;基于多种关系的综合性专利网络构建和分析,获得越来越多的关注,未来有可能成为新兴研究方向。展开更多
Monkey language models are defined for Chi-nese Phrase Networks, and scale-free features of Chinese Phrase Networks are uncovered. It is pointed out that the ratio of average degree to the total number of nodes ( k /N...Monkey language models are defined for Chi-nese Phrase Networks, and scale-free features of Chinese Phrase Networks are uncovered. It is pointed out that the ratio of average degree to the total number of nodes ( k /N ) is close to a constant. Simulation for the evolution of phrase networks indicates that one of the important reasons for power law distributions is the word selection frequency, which, when tuned aptly, can make the monkey language present similar statistic traits as that of natural languages. Power law tails emerge at large k, and the exponent is about 6. Comparison between monkey model and natural language shows that humans are able to use Chinese words resources in more effective and compact ways to express their inten-tions. All the results demonstrate an important fact that the least effort principle is the basis of Chinese Phrase Networks.展开更多
文摘【目的】分析国内外专利网络研究进展,梳理研究现状、发现研究问题和研判研究趋势。【文献范围】分别以"Patent Network"和"专利网络"为主题在Web of Science核心集和CNKI核心期刊库中检索,通过去重、去除不相关文献后,共检索到英文论文465篇,中文论文196篇,分析其中代表性论文106篇。【方法】首先,利用团渗透重叠社区发现算法对"专利网络"关键词共现网络进行主题挖掘,分析中英文热点研究主题;其次,对热点研究主题下的高被引论文进行述评。【结果】综合现有研究,专利网络构建方法主要有合作关系、引用关系、技术转移关系、技术相似关系等,主流研究方法有社会网络分析、复杂网络和文本挖掘等。【局限】仅对热点研究领域的高被引代表性论文进行分析,未能覆盖全部研究主题和文献。【结论】专利网络研究尚未形成系统性的理论和方法体系,新兴研究方法的应用仍处于探索阶段。专利网络分析需向中观层面深入,网络演化机制、模型和仿真实验研究还需进一步加强。专利网络语义化分析倾向越来越明显;基于多种关系的综合性专利网络构建和分析,获得越来越多的关注,未来有可能成为新兴研究方向。
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.10771092)国家重点基础研究发展规划(973)(the National Grand Fundamental Research973Program of China under Grant No.2004CB318000)
文摘Monkey language models are defined for Chi-nese Phrase Networks, and scale-free features of Chinese Phrase Networks are uncovered. It is pointed out that the ratio of average degree to the total number of nodes ( k /N ) is close to a constant. Simulation for the evolution of phrase networks indicates that one of the important reasons for power law distributions is the word selection frequency, which, when tuned aptly, can make the monkey language present similar statistic traits as that of natural languages. Power law tails emerge at large k, and the exponent is about 6. Comparison between monkey model and natural language shows that humans are able to use Chinese words resources in more effective and compact ways to express their inten-tions. All the results demonstrate an important fact that the least effort principle is the basis of Chinese Phrase Networks.
