Research on Enhancing Technology Transfer Efficiency through Artificial Intelligence and Recommendation Algorithms

This paper adopts a language processing model and semantic recommendation model to realize the intelligent matching of scientific research achievements and market demand in the electrical equipment industry, aiming to improve the transformation process of scientific research and innovation achievements into practical applications. Through in-depth demand analysis, the key data characteristics of both market demand and scientific research achievement are defined, and the corresponding information feature database is constructed. Pre training based on Bert model can accurately understand the scientific and technological achievements, scientific and technological needs, scientific research literature, patent documents and other contents in the field of electrical equipment. On this basis, an LFM implicit semantic recommendation algorithm model is added to realize the accurate matching between scientific research achievements and market scientific and technological needs. It is the first time for this technology recommendation in the field of transformation of scientific and technological achievements of electrical equipment.