基于专利数据的技术主题扩散量化研究与实现

Measuring Diffusion of Technology Topics with Patent Data

【目的】基于专利数据对技术主题扩散进行量化研究,为提前发现或预判技术扩散提供线索。【方法】以技术主题为研究单元,基于专利引用关系构建技术扩散关系;融合技术扩散的强度、速度、广度等三个维度构建技术扩散综合测度指标;在此基础上,实现技术主题扩散量化测度模型。【结果】从石墨烯领域100个技术主题的扩散分析来看,模型可以快速遴选综合扩散度高的技术主题,如多种石墨烯制备方法、“石墨烯用于晶体管”等;模型的生成结果还包括扩散的具体方向,如“石墨烯用于散热”主题向“腔壳设备”等主题强力扩散,向“含锂复合氧化物”等主题快速扩散。【局限】对三个维度的技术扩散测度指标进行了线性归一化,未深入研究各指标权重。未来可以根据情报应用目的优化各指标的权重值,提升综合测度指标的鲁棒性。【结论】综合测度优化了单一扩散指标测度的不均衡性,技术主题扩散测度模型可以快速生成有效的情报信息。

[Objective] This paper tries to quantify the diffusion of technology topics based on patent data, aiming to predict their dissemination in advance. [Methods] First, we constructed the technology diffusion relationship with the patent citation data. Then,we constructed a comprehensive measuring index for technology diffusion from their strength, speed and breadth. Finally, we built the model measuring technology topic diffusion. [Results] We examined our model with 100 topics in the graphene field, which quickly identified topics with high comprehensive diffusion scores. We also found the diffusion directions of graphene patents. [Limitations] We only normalized three measuring indice for technology diffusion with Min-Max Scaling, while their weights not beening optimized for the applications. [Conclusions] The proposed model could help us find intelligence effectively with the help of multiple measurements.