Abstract
Patent data have been utilized for engineering design research for long because it contains massive amount of design information. Recent advances in artificial intelligence and data science present unprecedented opportunities to mine, analyse and make sense of patent data to develop design theory and methodology. Herein, we survey the patent-for-design literature by their contributions to design theories, methods, tools, and strategies, as well as different forms of patent data and various methods. Our review sheds light on promising future research directions for the field.
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Jiang, S., Sarica, S., Song, B., Hu, J., & Luo, J. (2022). Patent Data for Engineering Design: A Review. In Proceedings of the Design Society (Vol. 2, pp. 723–732). Cambridge University Press. https://doi.org/10.1017/pds.2022.74
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