Semantic and relational spaces in science of science: deep learning models for article vectorisation
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DOI: 10.1007/s11192-021-03984-1
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- Yiqin Lv & Zheng Xie & Xiaojing Zuo & Yiping Song, 2022. "A multi-view method of scientific paper classification via heterogeneous graph embeddings," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4847-4872, August.
- Barbara McGillivray & Gard B. Jenset & Khalid Salama & Donna Schut, 2022. "Investigating patterns of change, stability, and interaction among scientific disciplines using embeddings," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
- Yuan Chih Fu & Marcelo Marques & Yuen-Hsien Tseng & Justin J. W. Powell & David P. Baker, 2022. "An evolving international research collaboration network: spatial and thematic developments in co-authored higher education research, 1998–2018," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1403-1429, March.
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Keywords
Embeddings; Science of science; Deep learning; Graph neural networks; Semantic space; Relational space;All these keywords.
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