3D建模领域专利引用网络度中心性数据

在专利导航等专利分析中，运用专利引用网络进行技术路径分析是一个重要工作，但是专利和专利之间的引用关系是错综复杂的网络关系，如何将网络结构简化并提炼出核心专利是一个关键问题。计算出3D建模领域中各个专利的度中心性后，可以用来反映该专利在引用网络中的重要性或中心性，对于选出该领域的核心专利和绘制专利技术路线图有重要意义。1、数据采集:运用专业专利数据检索工具，用关键词检索式锁定主题，采集3D建模领域的专利数据，包括公开号、标题、申请日期、引用专利、引用专利数量、被引用专利和被引用专利数量。2、数据处理:将简单同族专利合并，错误、重复数据去除等，形成初始化专利网络数据集;3、数据加工:要在专利网络中识别出具有重要影响力的网络节点，采用度中心性算法，将引用专利数量和被引用专利数量求和作为度中心性。C(v)=d_in (v)+d_out (v)，其中：C(v)是度中心性，d_in (v)是入度即专利被引用次数，d_out (v)是出度即专利引用次数。度中心性越高，说明该专利在专利网络中的影响力越大，代表该专利的创新性或重要性较高。例如，如果一个专利被大量其他专利引用，那么它可能是一个关键的创新或者是个重要的技术基础。

In patent analysis scenarios such as patent navigation, using patent citation networks for technical pathway analysis is a critical task. However, the citation relationships between patents form a complex network, and how to simplify the network structure and extract core patents remains a key challenge. Calculating the degree centrality of each patent in the 3D modeling field can reflect the importance or centrality of the patent within the citation network, which is of great significance for selecting core patents in this field and drawing patent technology roadmaps.
1. Data Collection: Use professional patent data retrieval tools and keyword search queries to lock onto the target theme, and collect patent data in the 3D modeling field, including publication numbers, titles, application dates, cited patents, number of cited patents, citing patents, and number of citing patents.
2. Data Preprocessing: Merge simple patent families, remove erroneous and duplicate data, and other similar operations to form an initial patent network dataset.
3. Data Processing: To identify network nodes with significant influence in the patent network, the degree centrality algorithm is adopted, where the degree centrality is calculated as the sum of the number of cited patents and the number of citing patents. The formula is C(v) = d_in(v) + d_out(v), where: C(v) represents the degree centrality, d_in(v) is the in-degree, i.e., the number of times the patent is cited by others, and d_out(v) is the out-degree, i.e., the number of times the patent cites other patents. A higher degree centrality indicates greater influence of the patent in the patent network, representing higher innovativeness or importance of the patent. For example, if a patent is cited by a large number of other patents, it may represent a key innovation or an important technical foundation.