Subjects: Statistics >> Social Statistics submitted time 2024-05-18 Cooperative journals: 《中国科学院院刊》
Abstract： For the first time, this study draws an Innovation Science Structure Map using the scientific structure mapping analysis method. It takes Essential Science Indicators (ESI) highly cited papers referenced in patents as the foundatial analyzing data, revealing the impact of leading-edge fundamental research on the development of technological innovation worldwide. It identifies the hotspot areas that are driving the advancement of technological innovation and compares the performance between China and the United States in these areas, providing robust data support for informed scientific decision-making. The analysis reveals that papers with a high number of patent references are primarily concentrated in emerging biotechnology and biomedical fields, as well as in new information technology, energy, and materials sectors that are likely to trigger disruptive technological innovations. There is a noticeable growth trend in China for papers with high citation counts referenced in patents, with a five-year cumulative growth exceeding 60%, but the total number is still less than half of that in the United States. The number of papers from China in many research hotspots closely associated with technological innovation is higher than that of the United States. Still, the count of papers referenced in patents is usually lower. The United States tends to fundamental research that influences technological innovation, leading more towards industrial transformation-related R&D activities, and involves a large number of enterprises.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-10-08 Cooperative journals: 《知识管理论坛》
Abstract： [Purpose/significance] Research on the contribution of the number of patent families to the value of patents can provide an important reference for patents strategy layout optimization and patent value evaluation. [Methods/process] Taking the new clean solar energy field as an example, we identified high-value and low-value patent data sets, and designed experiments on patent family size differences between high-value patents and low-value patents. Finally, then SPSS 22 was used to verify the model. [Results/conclusion] Empirical research have shown that the contribution of the number of patent families to the value of patents is not invariable. With the continuous expansion of the patent families, the proportion of patent families is no longer significant difference between high-value patents and low-value patents. At this time, the increase in the number of patent families has significantly reduced the contribution to patent value.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-27 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The identification of key research directions (KRDs) is significant to the management of scientific research and the formulation of policy. Existing methods of quantitative analysis mainly used indicators based on novelty, growth and other characteristics to identify and recommend KRDs. This paper used the relationships of research directions further and identified KRDs from network topology and characteristic two dimensions. [Method/process] On the basis of the building of citation network of papers in a field, a large-scale network clustering algorithm was used to detect research directions, and the topic association network was built. Then, identification algorithms of important nodes in complex networks were used to identify KRDs from the dimension of network topology, and an index system of selecting KRDs was constructed by combining three indicators of characteristic dimension, including novelty index, growth index and H-index. [Result/conclusion] After an empirical analysis of the field of nanotechnology, with the experts' interpretation, the paper concluded that growth index, Gefura and weighted PageRank are more objective and stable. Finally, 208 KRDs were identified by synthetically using above three indicators.
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》
Abstract： 2022 Technology Focus report developed by the Institutes of Science and Development, Chinese Academy of Sciences (CASISD), is based on the role of “Technology Focus” in the fields of information, energy, life and material manufacturing in the new technological revolution. We select and determine “20 High-impact Patented Technology Focus” from the 32 “Technology Focus” areas that are highlighted in the report. It briefly describes the basic meaning, technological innovation challenges, and the research path. Based on the distribution of comprehensive influence scores of patent data in “Technology Focus”, it reveals the technical innovation points and the characteristics of the national institutions of the patents with higher scores. Finally, three conclusions are given: (1) the technology focus characterizes the “difficulties” and “pain points” of industrial technological innovation in many fields around the world; (2) developed countries in science and technology occupy the commanding heights of most “Technology Focus”; and (3) the patent patent ownership institutions in the “Technology Focus” are leaders in industrial technological innovation.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】结合链路预测与机器学习, 提出推荐未来科研合作的新方法, 以提高单独基于链路预测方法的推荐精确度。【方法】构建加权作者合作网, 以不同的链路预测指标作为特征输入, 运用极端随机树(Extremely Randomized Trees, ET)机器学习算法训练分类, 并利用遍历算法求取分类结果的最优权重组合, 选取TOP 准确度的预测作为合作推荐结果。【结果】选取纳米科技领域2008 年–2010 年SCI 论文数据进行实证。在城市合作推荐中, 改进的ET 方法优于已有方法, 有良好的推荐成功率; 预测方法受网络结构等因素影响较小, 适用范围更广泛。【局限】科研合作受合作动机、地域、语言等诸多因素影响, 加权作者合作网没有反映在一篇论文中同城市、同机构的多个作者, 也没有反映上述因素。【结论】改进算法能够比单个预测指标产生更准确的合作推荐建议, 也为推广到大学等机构、个人等更微观的应用层面提供参考。
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】降低文献–作者二分网络在投影为合著网络过程中的信息丢失影响, 形成适应特定二分网络的合著关系预测指标和方法, 提高预测准确率和结果可解释性。【方法】首先构建文献–作者二分网络及其投影合著网络; 接着抽取二分网络中的二阶路径和三阶路径表示作者间的关联关系; 最后利用逻辑回归方法学习不同路径对于合著关系预测的贡献, 由此形成文献–作者二分网络中基于路径组合的合著关系预测指标。【结果】在图书情报领域的实验证实, 文献–作者二分网络在投影为合著网络过程中存在较大的信息丢失, 并以合著关系预测准确率变化进行定量计算; 逻辑回归方法适合学习不同路径对于合著关系预测的贡献, 由此形成的路径组合指标准确率远远高出其他指标, 并且预测结果更易解释。【局限】其他的多阶路径尚未引入到该模型中, 方法通用性还需在其他领域进行验证。【结论】合著关系预测应直接在文献–作者二分网络上进行, 以降低投影过程中的信息丢失影响; 文献–作者二分网络上的路径组合指标是合著关系预测的最优指标; 该方法可扩展应用到其他类型的二分网络中, 如专利–发明人二分网络。
Subjects: Library Science，Information Science >> Information Science submitted time 2017-10-11 Cooperative journals: 《数据分析与知识发现》
Abstract： [Objective] This paper aims to establish an automatic method to identify research area groups and outline the science map quickly. [Methods] First, we used feature words to measure topic similarity, and then divided adjacent research areas with similar/related topics into groups. Second, we designed an effectiveness evaluation index to compare different optimal parameters combination. [Results] The proposed method could identify research area groups in science maps effectively. [Limitations] Our study was conducted with data from Mapping Science Structure 2015. More research is needed to investigate the proposed method’s compatibility with other cases. [Conclusions] The proposed method could automatically identify research area groups in the science map.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-10-11 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】设计并实现基于模型–视图–控制器(MVC)前端AngularJS 框架的可视化组件ng-info-chart。【应用背景】优秀的情报分析平台往往需要使用多个复杂的可视化图谱组合展示分析结果, 需要更有效地构建复杂的、支持大量交互操作的网页端情报分析可视化图谱。【方法】ng-info-chart 集成多种可视化图谱, 使用AngularJS 自定义扩展标签统一封装, 通过自定义HTML 标签直接在页面中调用绘图方法。【结果】ng-info-chart 可视化组件随着研究团队情报分析项目不断深入与完善, 现已集成5 个第三方可视化类库中11 种可视化图谱, 支持IE9+、Firefox 等主流桌面浏览器。【结论】利用可视化组件实现数据异步获取、自动检测数据变化与实时图谱绘制等功能, 极大简化了情报分析系统中复杂可视化图谱的开发工作。
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