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专利信息的复杂性决定了研究专利问题需要从多个关系层面共同进行观察。文章介绍了一种基于多重关系整合的专利网络分析方法,即充分利用各种层间关系构建立体的、多维度的多重关系网络,并在该网络框架下进行凝聚子群划分、核心专利的识别等专利分析。通过构建基于多重关系整合的专利网络,能够促进整个专利数据分析的全面性与准确性,构建多模网络分析指标可以更好地捕捉到个体在组织中的重要性,且能比单一层次内的分析获得更多信息。所得结论可为相关领域的战略选择提供理论依据和实践指导。
The complexity of patent information determines that the study of patent issues needs to be jointly observed from multiple levels of relationship. This paper introduces a patent network analysis method based on multiple relationship integration, which makes full use of the various layers to build a multi-dimensional multi-dimensional relationship network, and under the framework of the network cohesion subgroups, the core of the patent identification Other patent analysis. By constructing a patent network based on multiple relationships and integration, the comprehensiveness and accuracy of the entire patent data analysis can be promoted. The construction of multi-mode network analysis indexes can better capture the importance of an individual in the organization and can be better than the single-level Analyze for more information. The conclusions can provide theoretical basis and practical guidance for the strategic choices in related fields.