A set in Rd is called regular if its Hausdorff dimension coincides with its upper box counting dimension. It is proved that a random graph-directed self-similar set is regular a.e..
We propose a new approach to the investigation of deterministic self-similar networks by using contractive iterated multifunction systems (briefly IMSs). Our paper focuses on the generalized version of two graph model...We propose a new approach to the investigation of deterministic self-similar networks by using contractive iterated multifunction systems (briefly IMSs). Our paper focuses on the generalized version of two graph models introduced by Barabási, Ravasz and Vicsek ([1] [2]). We generalize the graph models using stars and cliques: both algorithm construct graph sequences such that the next iteration is always based on n replicas of the current iteration, where n is the size of the initial graph structure, being a star or a clique. We analyze these self-similar graph sequences using IMSs in function of the size of the initial star and clique, respectively. Our research uses the Cantor set for the description of the fixed set of these IMSs, which we interpret as the limit object of the analyzed self-similar networks.展开更多
同一领域产品的专利技术具有高技术关联度等特征,企业在生产经营活动中面临着专利侵权的潜在风险,立足于企业专利侵权预警的实际需求,高效、准确地检测产品存在的专利侵权风险具有重要意义。由此,本文提出了专利侵权风险预警模型,该模...同一领域产品的专利技术具有高技术关联度等特征,企业在生产经营活动中面临着专利侵权的潜在风险,立足于企业专利侵权预警的实际需求,高效、准确地检测产品存在的专利侵权风险具有重要意义。由此,本文提出了专利侵权风险预警模型,该模型重新定义了领域专利知识图谱、产品技术方案图谱的模式层,涵盖了组件实体、结构实体和功效实体三类实体类型,以及组成关系、相对位置关系、连接关系和功效达成关系四类实体关系;基于BERT(bidirectional encoder representations from transformers)和BiLSTM(bi-directional long short-term memory)模型构建专利知识图谱和产品技术方案知识图谱;基于ComplEx模型实现知识图谱的嵌入,实现产品和专利技术之间相似度的量化计算,并根据专利侵权风险指数做出侵权预警。以空气加湿器和耳机两类产品进行实证研究,专利侵权预警准确率为86.67%,具有一定的应用价值。展开更多
随着数据来源方式的多样化发展,多视图聚类成为研究热点。大多数算法过于专注利用图结构寻求一致表示,却忽视了如何学习图结构本身;此外,一些方法通常基于固定视图进行算法优化。为了解决这些问题,提出了一种基于相似图投影学习的多视...随着数据来源方式的多样化发展,多视图聚类成为研究热点。大多数算法过于专注利用图结构寻求一致表示,却忽视了如何学习图结构本身;此外,一些方法通常基于固定视图进行算法优化。为了解决这些问题,提出了一种基于相似图投影学习的多视图聚类算法(multi-view clustering based on similarity graph projection learning, MCSGP),通过利用投影图有效地融合了全局结构信息和局部潜在信息到一个共识图中,而不仅是追求每个视图与共识图的一致性。通过在共识图矩阵的图拉普拉斯矩阵上施加秩约束,该算法能够自然地将数据点划分到所需数量的簇中。在两个人工数据集和七个真实数据集的实验中,MCSGP算法在人工数据集上的聚类效果表现出色,同时在涉及21个指标的真实数据集中,有17个指标达到了最优水平,从而充分证明了该算法的优越性能。展开更多
文摘A set in Rd is called regular if its Hausdorff dimension coincides with its upper box counting dimension. It is proved that a random graph-directed self-similar set is regular a.e..
文摘We propose a new approach to the investigation of deterministic self-similar networks by using contractive iterated multifunction systems (briefly IMSs). Our paper focuses on the generalized version of two graph models introduced by Barabási, Ravasz and Vicsek ([1] [2]). We generalize the graph models using stars and cliques: both algorithm construct graph sequences such that the next iteration is always based on n replicas of the current iteration, where n is the size of the initial graph structure, being a star or a clique. We analyze these self-similar graph sequences using IMSs in function of the size of the initial star and clique, respectively. Our research uses the Cantor set for the description of the fixed set of these IMSs, which we interpret as the limit object of the analyzed self-similar networks.
文摘同一领域产品的专利技术具有高技术关联度等特征,企业在生产经营活动中面临着专利侵权的潜在风险,立足于企业专利侵权预警的实际需求,高效、准确地检测产品存在的专利侵权风险具有重要意义。由此,本文提出了专利侵权风险预警模型,该模型重新定义了领域专利知识图谱、产品技术方案图谱的模式层,涵盖了组件实体、结构实体和功效实体三类实体类型,以及组成关系、相对位置关系、连接关系和功效达成关系四类实体关系;基于BERT(bidirectional encoder representations from transformers)和BiLSTM(bi-directional long short-term memory)模型构建专利知识图谱和产品技术方案知识图谱;基于ComplEx模型实现知识图谱的嵌入,实现产品和专利技术之间相似度的量化计算,并根据专利侵权风险指数做出侵权预警。以空气加湿器和耳机两类产品进行实证研究,专利侵权预警准确率为86.67%,具有一定的应用价值。
文摘随着数据来源方式的多样化发展,多视图聚类成为研究热点。大多数算法过于专注利用图结构寻求一致表示,却忽视了如何学习图结构本身;此外,一些方法通常基于固定视图进行算法优化。为了解决这些问题,提出了一种基于相似图投影学习的多视图聚类算法(multi-view clustering based on similarity graph projection learning, MCSGP),通过利用投影图有效地融合了全局结构信息和局部潜在信息到一个共识图中,而不仅是追求每个视图与共识图的一致性。通过在共识图矩阵的图拉普拉斯矩阵上施加秩约束,该算法能够自然地将数据点划分到所需数量的簇中。在两个人工数据集和七个真实数据集的实验中,MCSGP算法在人工数据集上的聚类效果表现出色,同时在涉及21个指标的真实数据集中,有17个指标达到了最优水平,从而充分证明了该算法的优越性能。
