Supervised Machine Learning for Matchmaking in Digital Business Ecosystems and Platforms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s10796-022-10357-3.pdf
Reference43 articles.
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3. Cassar, G., Barnaghi, P., & Moessner, K. (2013). Probabilistic matchmaking methods for automated service discovery. IEEE Transactions on Services Computing, 7(4), 654–666.
4. Celik, D., & Elci, A. (2005). Searching semantic Web services: An intelligent agent approach using semantic enhancement of client input term (s) and matchmaking step. In International conference on computational intelligence for modelling, control and automation and international conference on intelligent agents, web technologies and internet commerce (CIMCA-IAWTIC’06) (vol. 2, pp. 916-922). IEEE.
5. Chen, Y., Li, X., Liu, J., & Ying, Z. (2018). Recommendation system for adaptive learning. Applied Psychological Measurement, 42(1), 24–41.
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