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| Examining Novelty of Technological Topics Based on Combination Probabilities |
| Sun Xiaoling, Chen Na, Ding Kun |
| Institute of Science of Science and S&T Management, Dalian University of Technology, Dalian 116024 |
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Abstract Technological novelty is considered to be an important driving force to facilitate the breakthrough of innovation. Comprehensively measuring the novelty of technological topics can help identify novelty patents as early as possible and reduce the risk of delayed identification of emerging key technologies. As a knowledge element of technology, subject headings can adequately represent the subject content and methods of technological inventions. This study proposes a method to measure the novelty of technological topics from the perspective of combination probability, which integrates the direct combination times, indirect combination probability, and semantic similarity of patent subject words. Taking invention patents in the field of artificial intelligence as an example, it is verified that the method can capture the potential distance between subject word combinations, as well as identify more novelty combinations than a single indicator. The study’s findings indicate that high novelty/high conventional patents exhibit a higher average number of citations, and the high novelty patents exhibit the highest probability of becoming highly cited patents.
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Received: 09 October 2021
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