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高级工程师

性别: 男

毕业院校: 大连理工大学

学位: 博士

所在单位: 计算机科学与技术学院

学科: 计算机应用技术

办公地点: 创新园大厦D0103房间

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基于HDP的汽车专利主题演化研究

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发表时间: 2022-10-10

发表刊物: 情报学报

期号: 9

页面范围: 944-951

ISSN号: 1000-0135

摘要: In recent years,the patent data is in explosive growth. Accurately extracting topic information from patent data and visualizing it is becoming an important research direction. The research of the topic evolution of vehicle patent can dig out the potential development model,which has great importance to the related study. Here,we used the Hierarchical Dirichlet process (HDP) to cluster the patent data and mine splitting and merging of the topics by comparing the topics of each year and the topics with history data clustered by HDP. At last,we visualized the relationship of the topic information using stacked graph. We used the actual vehicle patent data in the experiment and discovered that there are three major topics of the vehicle patent data. There are splitting and merging among different topics,shrinking of the topic,expanding of the topic,newborn of the topic and perishing of the topic. We also found that after 2006 the field of vehicle safety and new energy sources for vehicle became to individual topics and showed increasing trend year by year.

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