Explanation-Based Negotiation Protocol for Nutrition Virtual Coaching

Author:

Buzcu BerkORCID,Varadhajaran VanithaORCID,Tchappi IgorORCID,Najjar AmroORCID,Calvaresi DavideORCID,Aydoğan ReyhanORCID

Publisher

Springer International Publishing

Reference31 articles.

1. Alexandra, V.A., Badica, C.: Recommender systems: an explainable AI perspective. In: 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA), pp. 1–6. IEEE (08 2021)

2. Anjomshoae, S., Najjar, A., Calvaresi, D., Främling, K.: Explainable agents and robots: results from a systematic literature review. In: AAMAS, Montreal, Canada, May 13–17, pp. 1078–1088 (2019)

3. Studies in Computational Intelligence;R Aydoğan,2017

4. Ayub, R., Ghazanfar, M.A., Maqsood, M., Saleem, A.: A jaccard base similarity measure to improve performance of CF based recommender systems, pp. 1–6 (01 2018). https://doi.org/10.1109/ICOIN.2018.8343073

5. Chen, M., Jia, X., Gorbonos, E., Hoang, C.T., Yu, X., Liu, Y.: Eating healthier: exploring nutrition information for healthier recipe recommendation. Inf. Process. Manage. 57(6), 102051 (2020)

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