Abstract
High-quality patents have high technical value and market competitive advantage. Faced with the huge number of patent data, how to rapidly and efficiently identify the quality of patents from the patent announcement is a crucial research issue at present. Therefore, it is reasonable to predict that, big data based techniques will be the best method to exploit this kind of data. The patents authorized by CNIPA (China National Intellectual Property Administration) are taken as the research object. This study chooses several types of patent evaluation indicators and uses EWM (The Entropy Weight Method) to calculate the weight of each indicator. The study determines a correction coefficient to enhance the usability and provides the final quality score of each patent. The evaluating formula is provided. In this study, easily accessible patent indicators are used, which makes it easier to evaluate the quality of patents. By this method, rapidly evaluating the patent quality only by its basic announcement data is feasible, which solves the limitation that laborious access to advanced indicators.
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