以专利引证网络为载体,从知识基因稳定性、遗传性以及变异性等基本特征出发,提出一种基于subject-action-object三元组的知识基因提取方法.应用连接度算法分析专利引证关系,挖掘引证专利和被引专利之间继承和发展的知识流,建立知识进化...以专利引证网络为载体,从知识基因稳定性、遗传性以及变异性等基本特征出发,提出一种基于subject-action-object三元组的知识基因提取方法.应用连接度算法分析专利引证关系,挖掘引证专利和被引专利之间继承和发展的知识流,建立知识进化轨迹;利用文本语法分析技术,从专利权利要求书中提取subject-action-object三元组;基于语义词库WordNet进行语义加工,计算语义相似度,合并同义的subject-action-object三元组,绘制知识基因图谱.从美国专利数据库中采集了5 073项1975—1999年授权的数据挖掘领域的相关专利,分析了专利的地区分布情况和年度分布情况.从NBER(National Bureau of Economic Research)的专利数据集中查询得到专利引证关系,利用网络分析软件Pajek构建专利引证网络,作为实验数据样本,对所提出的知识基因提取方法进行验证.实验结果表明:所提取的subject-action-object三元组具备了知识基因稳定性、遗传性和变异性等特征,可以作为知识基因的一种表现形式.展开更多
目的本研究旨在识别抑郁症主客观认知功能的核心症状,同时识别出认知功能与社会功能相关症状。方法选取2023年2月—2024年10月在山东省戴庄医院就诊的181名抑郁症患者为研究对象。抑郁症认知损害5项问卷(Five-item Perceived Deficits Q...目的本研究旨在识别抑郁症主客观认知功能的核心症状,同时识别出认知功能与社会功能相关症状。方法选取2023年2月—2024年10月在山东省戴庄医院就诊的181名抑郁症患者为研究对象。抑郁症认知损害5项问卷(Five-item Perceived Deficits Questionnaire for Depression,PDQ-5-D)、中国简版神经认知成套测验(Chinese Version of Brief Neurocognitive Test Battery,C-BCT)、席汉残疾量表(Sheehan Disability Scale,SDS)用于评定主观认知功能、客观认知功能以及社会功能。使用R软件对网络进行统计分析和可视化。结果大脑空白为主观认知网络及客观认知网络中的中心症状和桥接症状。难条理化与社会功能之间存在相关性。性别与网络全局强度、边权重分布或个体边权重无关。结论大脑空白是整个主客观认知网的核心症状。难条理化与社会功能间关联系数最高。关注大脑空白症状,可能在一定程度上改善抑郁症患者的认知功能。通过及早干预并改善难条理化症状,或将更好改善患者的社会功能。展开更多
【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序...【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)的关键节点识别方法。首先,提出节点相似中心性指标,通过融合关联度与强度平衡局部拓扑与全局影响力;然后,构建整合网络拓扑、数据关联及节点相似性的多指标评价体系,全面刻画节点重要性;接着,提出双层权重优化策略,结合层次分析法(Analytic Hierarchy Process, AHP)和指标相关性定权法(Criteria Importance Through Intercriteria Correlation, CRITIC)方法,融合主客观权重,提升评估科学性;最后,结合TOPSIS评估方法进行节点重要性的综合评估。【结果】实验基于团队构建的不同规模的地表系统科学数据有向加权关联网络,结合加权易感-感染-恢复(SIR)模型进行实验验证,结果表明:与传统网络加权中心性以及基于主观或客观权重的TOPSIS等方法相比,本文方法在肯德尔相关系数值和TOP-K命中率方面表现更优,且在网络中展现强鲁棒性。【结论】该方法为地表系统科学数据网络分析提供了新方法,可支撑智能推荐、资源优化及系统脆弱性分析等实际应用,助力地球系统科学研究的深度发展。展开更多
Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values, a formalized model of subjective trust is introduced by which we ...Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values, a formalized model of subjective trust is introduced by which we can transform between qualitative reputation and quantitative voting data. The present paper brings forward algorithms to compute direct trust and recommender trust. Further more, an effective similarity measuring method used to distinguish two users＇ reputation on knowledge level is also proposed. The given model properly settles the uncertainty and fuzziness properties of subjective trust which is always the weakness of traditional subjective trust model, and provides a step in the direction of proper understanding and definition of human trust.展开更多
Purpose: This paper intends to explore methodologies and indicators for the analysis of overlapping structures and evolution properties in a co-citation network, and provide reference for overlapping structure analysi...Purpose: This paper intends to explore methodologies and indicators for the analysis of overlapping structures and evolution properties in a co-citation network, and provide reference for overlapping structure analysis of other scientific networks.Design/methodology/approach: The Q-value variance is defined to achieve overlapping structures of different levels in the scientific networks. At the same time, analyses for time correlation variance and subject correlation variance are used to present the formation of overlapping structures in scientific networks. As a test, a co-citation network of highly cited papers on Molecular Biology & Genetics from Essential Science Indicator(ESI) is taken as an example for an empirical analysis.Findings: Our research showed that the Q-value variance is effective for achieving the desired overlapping structures. Meanwhile, the time correlation variance and subject correlation variance are equally useful for uncovering the evolution progress of scientific research, and the properties of overlapping structures in the research of co-citation network as well.Research limitations: In this paper, the theoretical analysis and verification of time and subject correlation variances are still at its initial stage. Further studies in this regard need to take actual evolution of research areas into consideration.Practical implications: Evolution properties of overlapping structures pave the way for overlapping and evolution analysis of disciplines or areas, this study is of practical value for the planning of scientific and technical innovation.Originality/value: This paper proposes an analytical method of time correlation variance and subject correlation variance based on the evolution properties of overlapping structures, which would provide the foundation for the evolution analysis of disciplines and interdisciplinary research.展开更多
文摘以专利引证网络为载体,从知识基因稳定性、遗传性以及变异性等基本特征出发,提出一种基于subject-action-object三元组的知识基因提取方法.应用连接度算法分析专利引证关系,挖掘引证专利和被引专利之间继承和发展的知识流,建立知识进化轨迹;利用文本语法分析技术,从专利权利要求书中提取subject-action-object三元组;基于语义词库WordNet进行语义加工,计算语义相似度,合并同义的subject-action-object三元组,绘制知识基因图谱.从美国专利数据库中采集了5 073项1975—1999年授权的数据挖掘领域的相关专利,分析了专利的地区分布情况和年度分布情况.从NBER(National Bureau of Economic Research)的专利数据集中查询得到专利引证关系,利用网络分析软件Pajek构建专利引证网络,作为实验数据样本,对所提出的知识基因提取方法进行验证.实验结果表明:所提取的subject-action-object三元组具备了知识基因稳定性、遗传性和变异性等特征,可以作为知识基因的一种表现形式.
文摘目的本研究旨在识别抑郁症主客观认知功能的核心症状,同时识别出认知功能与社会功能相关症状。方法选取2023年2月—2024年10月在山东省戴庄医院就诊的181名抑郁症患者为研究对象。抑郁症认知损害5项问卷(Five-item Perceived Deficits Questionnaire for Depression,PDQ-5-D)、中国简版神经认知成套测验(Chinese Version of Brief Neurocognitive Test Battery,C-BCT)、席汉残疾量表(Sheehan Disability Scale,SDS)用于评定主观认知功能、客观认知功能以及社会功能。使用R软件对网络进行统计分析和可视化。结果大脑空白为主观认知网络及客观认知网络中的中心症状和桥接症状。难条理化与社会功能之间存在相关性。性别与网络全局强度、边权重分布或个体边权重无关。结论大脑空白是整个主客观认知网的核心症状。难条理化与社会功能间关联系数最高。关注大脑空白症状,可能在一定程度上改善抑郁症患者的认知功能。通过及早干预并改善难条理化症状,或将更好改善患者的社会功能。
文摘【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)的关键节点识别方法。首先,提出节点相似中心性指标,通过融合关联度与强度平衡局部拓扑与全局影响力;然后,构建整合网络拓扑、数据关联及节点相似性的多指标评价体系,全面刻画节点重要性;接着,提出双层权重优化策略,结合层次分析法(Analytic Hierarchy Process, AHP)和指标相关性定权法(Criteria Importance Through Intercriteria Correlation, CRITIC)方法,融合主客观权重,提升评估科学性;最后,结合TOPSIS评估方法进行节点重要性的综合评估。【结果】实验基于团队构建的不同规模的地表系统科学数据有向加权关联网络,结合加权易感-感染-恢复(SIR)模型进行实验验证,结果表明:与传统网络加权中心性以及基于主观或客观权重的TOPSIS等方法相比,本文方法在肯德尔相关系数值和TOP-K命中率方面表现更优,且在网络中展现强鲁棒性。【结论】该方法为地表系统科学数据网络分析提供了新方法,可支撑智能推荐、资源优化及系统脆弱性分析等实际应用,助力地球系统科学研究的深度发展。
基金Supported bythe National Basic Research Programof China (973 Program) (G2004CB719401) National Natural Sci-ence Foundation of China (60496323 ,60375016)
文摘Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values, a formalized model of subjective trust is introduced by which we can transform between qualitative reputation and quantitative voting data. The present paper brings forward algorithms to compute direct trust and recommender trust. Further more, an effective similarity measuring method used to distinguish two users＇ reputation on knowledge level is also proposed. The given model properly settles the uncertainty and fuzziness properties of subjective trust which is always the weakness of traditional subjective trust model, and provides a step in the direction of proper understanding and definition of human trust.
基金supported by the National Science Library of Chinese Academy of Sciences
文摘Purpose: This paper intends to explore methodologies and indicators for the analysis of overlapping structures and evolution properties in a co-citation network, and provide reference for overlapping structure analysis of other scientific networks.Design/methodology/approach: The Q-value variance is defined to achieve overlapping structures of different levels in the scientific networks. At the same time, analyses for time correlation variance and subject correlation variance are used to present the formation of overlapping structures in scientific networks. As a test, a co-citation network of highly cited papers on Molecular Biology & Genetics from Essential Science Indicator(ESI) is taken as an example for an empirical analysis.Findings: Our research showed that the Q-value variance is effective for achieving the desired overlapping structures. Meanwhile, the time correlation variance and subject correlation variance are equally useful for uncovering the evolution progress of scientific research, and the properties of overlapping structures in the research of co-citation network as well.Research limitations: In this paper, the theoretical analysis and verification of time and subject correlation variances are still at its initial stage. Further studies in this regard need to take actual evolution of research areas into consideration.Practical implications: Evolution properties of overlapping structures pave the way for overlapping and evolution analysis of disciplines or areas, this study is of practical value for the planning of scientific and technical innovation.Originality/value: This paper proposes an analytical method of time correlation variance and subject correlation variance based on the evolution properties of overlapping structures, which would provide the foundation for the evolution analysis of disciplines and interdisciplinary research.
