Choosing the right collaboration partner for innovation: a framework based on topic analysis and link prediction
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DOI: 10.1007/s11192-022-04306-9
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Cited by:
- Li, Jing & Yu, Qian, 2024. "Scientists’ disciplinary characteristics and collaboration behaviour under the convergence paradigm: A multilevel network perspective," Journal of Informetrics, Elsevier, vol. 18(1).
- Wang, Liang & Li, Munan, 2024. "An exploration method for technology forecasting that combines link prediction with graph embedding: A case study on blockchain," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
- Xiuxiu Li & Mingyang Wang & Xu Liu, 2024. "Predicting collaborative relationship among scholars by integrating scholars’ content-based and structure-based features," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3225-3244, June.
- Csizmadia, Péter & Kosztyán, Zsolt Tibor & Fehérvölgyi, Beáta & Hausz, Frigyes, 2024. "Intézményi koncentráció és az innovációs hálózatok vizsgálata [Institutional concentration and innovation networks]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1351-1380.
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Keywords
Collaborative innovation; Partner selection; Topic analysis; Link prediction;All these keywords.
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