Research on the High Value Patent Identification System from the Perspective of the Full Cycle of Patent Formation
With the acceleration of China's economic transformation and upgrading,promoting intellectual property construction across the country has become an important issue in the innovation driven development strategy.Although China has become a major intellectual property country,it is not a strong intellectual property country.Therefore,building a comprehensive method for identifying high-value patents will help to accurately classify patent values,thereby more effectively improving patent layout,enhancing research and development efficiency,and formulating intellectual property strategies.This study selects the invention patent data of high-tech enterprises in Zhuhai City and proposes to construct high-value patent recognition indicators based on the full cycle process of patent formation,namely high-level technology research and development indicators,high-quality application confirmation indicators,and high return conversion application indicators.Based on three types of machine learning methods,namely support vector machine,neural network,and adaptive enhancement,a high-value patent recognition model is constructed and empirical analysis is conducted.This study aims to improve the high-value patent identification system and assist enterprises and decision-making departments in carrying out high-value patent identification work.
万方数据
维普
