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| Patent Infringement Risk Early Warning: Using Knowledge Graphs |
| Ding Shengchun, Qin Tianyun, Wang Yilin |
| Department of Information Management, School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094 |
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Abstract Patented technologies for products in the same field have characteristics such as high technical relevance and enterprises face the potential danger of patent infringement in their operations and production activities. Based on the actual needs of patent infringement early warning of enterprises, it is of great significance to efficiently and accurately detect the risk of patent infringement of products; thus, this study proposes a Patent Infringement Risk Early Warning Model. In this model, the schema layer of the domain patent knowledge graph and product knowledge graph are redefined, covering three types of entities: component entities, structural entities, and efficacy entities, as well as four types of entity relationships: composition relationship, relative position relationship, connection relationship, and efficacy achievement relationship. Patent and product technical scheme knowledge graphs are constructed based on the BERT and BiLSTM models. Based on the ComplEx model, the knowledge graph was embedded to achieve a quantitative calculation of the similarity between products and patented technologies, and an infringement warning was issued according to the patent infringement risk index. Two types of products, air humidifiers and earphones, were used for the empirical research, and the accuracy rate of patent infringement warnings was 86.67%, which has a certain application value.
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Received: 23 October 2023
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