关键词: 技术创新组合识别, 深度学习, SAO法, 语义挖掘, 专利分析

Abstract: [Purpose/Significance] With the rapid development of strategic emerging technology industries, how to identify technological innovation combinations with potential synergistic effect and clarify the core innovation relationships in the combination is an important prerequisite for effectively planning industrial development routes and enhancing industrial competitive advantages.[Method/Process] Guided by the theory of technology portfolio evolution, this paper based on patent data and proposed a recognition scheme of technological innovation combinations and evolution relationships, which combined algorithms such as deep learning, SAO semantic mining and CFDP. The study protocol was divided into 3 steps:The first step was to design a domain search strategy based on keywords and patent classification numbers and completed the cleaning and word segmentation of the acquired data; Then the study got the word vector semantic network of the technical topics in the domain through Word2Vec, and used the CFDP algorithm to identify potential innovation elements and combination methods; Finally, it deeply explored the core SAO structures in each portfolio, classified their evolutionary relationships through the LSTM deep learning algorithm, and explored the core innovation approach of technology, so as to effectively discover the potential technology chance in the domain.[Result/Conclusion] Taking the field of speech recognition as an example, through in-depth mining of DII patent text data in this field, the study has identified and tracked five types of potential technological innovation combinations and core innovation methods. And the study finds that the current speech recognition field, which is in the smart chip design, speech recognition algorithms, new scenarios and applications, has great potential for technological innovation in China.

Key words: technological innovation combination identification, deep learning, SAO, semantic mining, patent analysis