专利视角下融合多属性的技术创新主题挖掘方法 ——以芯片领域专利为例
Multi-attribute Mining Method for Technology Innovation Subject from the Perspective of Patent——The Case of Chip Patents
目的/意义] 使用融合多属性的量化方法,快速且有效地挖掘出领域内多个技术创新主题,为技术创新方向的确定提供借鉴。[方法/过程] 将LDA (Latent Dirichlet Allocation)主题模型与专利价值评价指标相结合,提出一种挖掘技术创新主题的量化方法。首先,综合运用TF-IDF、困惑度和四分位数法构建领域专利的LDA主题模型。然后,利用LDA输出的概率分布矩阵,结合专利价值评价指标(权利要求和IPC),构建量化指标体系。接着,选取芯片专利进行验证实验,计算量化指标并运用热力图对其可视化,识别出技术创新主题。最后,基于专利、LDA的输出矩阵、创新主题和量化指标之间的映射关系,进行专利筛选和技术创新主题的合理标记。[结果/结论] 通过邀请微电子领域专家和参考最新国内外芯片技术两种方式对实验结果进行评估,结果表明:融合多属性的领域技术创新主题挖掘方法能够快速且有效地挖掘出多个技术创新主题,在实践层面可以更好地为相关领域企业和科技工作者发现技术创新主题提供思路。
Purpose/significance] By combining multiple attributes, it can quickly and effectively dig out multiple technological innovation themes in the field, providing reference for the determination of technological innovation direction. [Method/process] This paper combined the LDA (Latent Dirichlet Allocation) topic model with the evaluation indicators of patent value, and proposed a quantitative method for mining patent innovation themes. First, TF-IDF, means of perplexity and quartile method were used to construct the LDA topic model of the domain patent to mine technological topics. Then, the probability distribution matrix output by LDA was combined with the evaluation indicators of patent value(claim and IPC) to construct a quantitative indicator system. Then, patents in the chip field were selected for verification experiments, quantitative indicators were calculated and visualized by heat map to identify the technological innovation themes in the field. Finally, based on the mapping relationship between patent, LDA output matrix, innovation theme and quantitative indicators, innovation patent screening and reasonable marking of technological innovation themes were carried out. [Result/conclusion] By inviting experts in the field of microelectronics and based on the latest chip technology at home and abroad to evaluate the experimental results. The scoring results show that the method of mining technology innovation topics with multiple attributes can mine multiple technology innovation topics quickly and effectively. At the practical level, it can better provide ideas for enterprises and scientists in related fields to technological innovation themes.
李慧、玄洪升
微电子学、集成电路
专利困惑度潜在狄利克雷分布量化指标体系技术创新主题
patentperplexityLDAquantitative indicatorstechnological innovation topics
李慧,玄洪升.专利视角下融合多属性的技术创新主题挖掘方法 ——以芯片领域专利为例[EB/OL].(2023-04-01)[2025-08-18].https://chinaxiv.org/abs/202304.00217.点此复制
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