Multi-attribute Mining Method for Technology Innovation Subject from the Perspective of Patent——The Case of Chip Patents postprint

Abstract: [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.