Knowledge graph enhanced citation recommendation model for patent examiners
Author:
Funder
Key-Area Research and Development Program of Guangdong Province
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11192-024-04966-9.pdf
Reference51 articles.
1. Alcácer, J., & Gittelman, M. (2006). Patent citations as a measure of knowledge flows: The influence of examiner citations. The Review of Economics and Statistics, 88(4), 774–779.
2. An, X., Li, J., Xu, S., Chen, L., & Sun, W. (2021). An improved patent similarity measurem-ent based on entities and semantic relations. Journal of Informetrics, 15(2), 101135. https://doi.org/10.1016/j.joi.2021.101135
3. Arts, S., Cassiman, B., & Gomez, J. C. (2018). Text matching to measure patent similarity. Strategic Management Journal, 39(1), 62–84. https://doi.org/10.1002/smj.2699
4. Arts, S., Hou, J., & Gomez, J. C. (2021). Natural language processing to identify the creation and impact of new technologies in patent text: Code, data, and new measures. Research Policy, 50(2), 104144. https://doi.org/10.1016/j.respol.2020.104144
5. Brooks, T. A. (1985). Private acts and public objects: An investigation of citer motivations. Journal of the American Society for Information Science, 36(4), 223–229. https://doi.org/10.1002/asi.4630360402
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