With the development of recommender systems (RSs), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. Multi-criteria recommender systems (MCRSs) are designed to provide personalized recommendations by considering user preferences in multiple attributes or criteria simultaneously. Unlike traditional RSs that typically focus on a single rating, these systems help users make more informed decisions by considering their diverse preferences and needs across various dimensions.

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[1] Yong Zheng, "OpenTable data with multi-criteria ratings", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/8avw-yk62. Accessed: Dec. 08, 2024.
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doi = {10.21227/8avw-yk62},
url = {http://dx.doi.org/10.21227/8avw-yk62},
author = {Yong Zheng },
publisher = {IEEE Dataport},
title = {OpenTable data with multi-criteria ratings},
year = {2024} }
TY - DATA
T1 - OpenTable data with multi-criteria ratings
AU - Yong Zheng
PY - 2024
PB - IEEE Dataport
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Yong Zheng. (2024). OpenTable data with multi-criteria ratings. IEEE Dataport. http://dx.doi.org/10.21227/8avw-yk62
Yong Zheng, 2024. OpenTable data with multi-criteria ratings. Available at: http://dx.doi.org/10.21227/8avw-yk62.
Yong Zheng. (2024). "OpenTable data with multi-criteria ratings." Web.
1. Yong Zheng. OpenTable data with multi-criteria ratings [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/8avw-yk62
Yong Zheng. "OpenTable data with multi-criteria ratings." doi: 10.21227/8avw-yk62