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An SAO-based approach to patent evaluation using TRIZ evolution trends

This paper proposes a new approach to evaluate future technological value of patents using TRIZ evolution trends. Previous studies using TRIZ evolution trends have determined patents with high evolutionary potential as high value technology in the future without considering relative importance of each TRIZ trend in a specific technology domain. Thus, previous approaches have limitations in that the importance of TRIZ evolution trends can be different according to the technology domain and current stage of the technology cycle of the technology domain. To overcome such limitations, we propose a method which can consider the priority of importance of TRIZ evolution trends and the technology cycle. To this end, we adopted an SAO-based text mining approach and semantic similarity measurement method.