Research on patent quality evaluation based on rough set and cloud model

The evaluation and identification of high-quality patents are urgently needed for the technological research and development and the transformation of achievements. Traditional researchers and analysts mainly focus on developing various patent quality indicators.However, there is a lack of relative research on how to apply these indicators to comprehensively evaluate patent quality. Therefore, this paper uses the rough set theory(RST) and multidimensional cloud model(MCM) to construct a comprehensive evaluation and grading system for patent quality (RST-MCM), which is used to comprehensively evaluate the quality of patents. First, by systematically summarizing the relevant literature on patent quality evaluation, we identify the influencing factors of patent quality in multiple dimensions and at multiple stages. Second, the patent quality evaluation index system is constructed by using RST to reduce redundant patent quality influencing factors and determine the evaluation index weights. Finally, the evaluation and grading of patent quality is completed with MCM. To validate the effectiveness of the research, RST-MCM is applied to the quality evaluation of patents in the construction engineering industry. The research results show that the accuracy rate of RST-MCM is 90.3%. The research will provide effective decision-making support for the formulation of technical strategies such as improving independent innovation capability and patent layout.