国家知识产权局刊登山东科创山东知识产权运营中心专利转化做法

Core Viewpoint - The Shandong Intellectual Property Operation Center has been recognized for its innovative practices in integrating artificial intelligence into the entire process of intellectual property management, thereby creating an efficient and intelligent ecosystem that supports industrial upgrading in Shandong Province [1][2]. Group 1: Operation Chain - The operation center has established a service network based on a three-level vertical linkage and a three-party horizontal collaboration model, enhancing the accessibility of professional intellectual property services to grassroots levels [2][3]. - Three sub-centers have been set up in Linyi, Weifang, and Tai'an, with additional workstations in counties like Yancheng and Yishui, forming a comprehensive service system [2][3]. Group 2: Demand Chain - The operation center focuses on actual technical needs of enterprises to guide research and patent conversion paths, conducting over 1,000 enterprise visits and identifying more than 500 technical needs [3][4]. - Collaborations have been established between companies and academic institutions to address specific technical challenges, such as the partnership between Kang Aite Chemical and Linyi University [3][4]. Group 3: Technology Chain - The introduction of AI technology has significantly improved the matching capability between a vast number of patents and enterprise needs, creating a "smart matching system" that integrates technology, patents, and talent [4][5]. - The operation center has built a resource database containing over 300,000 patent records, facilitating efficient connections between technology demands and available patents [4][5]. Group 4: Transformation Chain - The operation center has developed various innovative transformation models, such as "patent + project" and "patent + talent," to enhance industrial innovation and upgrade [5]. - Specific examples include assisting enterprises in applying for provincial-level manufacturing project championships and promoting technology transfer from universities to improve production processes [5].