Survey on the objectives of recommender systems: Measures, solutions, evaluation methodology, and new perspectives
Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …
variety of commercial applications to help users find favourite products. Research in the …
A hybrid probabilistic multiobjective evolutionary algorithm for commercial recommendation systems
As big-data-driven complex systems, commercial recommendation systems (RSs) have
been widely used in such companies as Amazon and Ebay. Their core aim is to maximize …
been widely used in such companies as Amazon and Ebay. Their core aim is to maximize …
Multi-objective optimization for location-based and preferences-aware recommendation
Location is of vital importance in recommender systems. This paper proposes a novel multi-
objective framework for location-based and preference-aware recommendation. Under this …
objective framework for location-based and preference-aware recommendation. Under this …
Multi-gradient descent for multi-objective recommender systems
N Milojkovic, D Antognini, G Bergamin… - arxiv preprint arxiv …, 2019 - arxiv.org
Recommender systems need to mirror the complexity of the environment they are applied in.
The more we know about what might benefit the user, the more objectives the recommender …
The more we know about what might benefit the user, the more objectives the recommender …
[HTML][HTML] A many objective commercial recommendation algorithm via Game-Based core node extraction
Y Sun, Y Cao, S Cheng, J Yang, W Shi, A Zhang… - Egyptian Informatics …, 2023 - Elsevier
The development of the recommendation system (RS) has been focused on improving the
accuracy of algorithms. As the number of new users grows, RS suffers from the cold start …
accuracy of algorithms. As the number of new users grows, RS suffers from the cold start …
A community division-based evolutionary algorithm for large-scale multi-objective recommendations
L Zhang, H Zhang, S Liu, C Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multi-objective evolutionary algorithms (MOEAs) have been demonstrated to be competitive
in recommender systems. In most of the exiting MOEA-based recommendation algorithms …
in recommender systems. In most of the exiting MOEA-based recommendation algorithms …
Pareto Set Learning for Multi-Objective Reinforcement Learning
E Liu, YC Wu, X Huang, C Gao, RJ Wang… - arxiv preprint arxiv …, 2025 - arxiv.org
Multi-objective decision-making problems have emerged in numerous real-world scenarios,
such as video games, navigation and robotics. Considering the clear advantages of …
such as video games, navigation and robotics. Considering the clear advantages of …
Multiobjective deep reinforcement learning for recommendation systems
Most existing recommendation systems (RSs) are primarily concerned about the accuracy of
rating prediction and only recommending popular items. However, other non-accuracy …
rating prediction and only recommending popular items. However, other non-accuracy …
A Multi-Population Based Evolutionary Algorithm for Many-Objective Recommendations
L Zhang, H Zhang, Z Chen, S Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multi-objective evolutionary algorithms (MOEAs) have been proved to be competitive in
recommender systems. As the application scenarios of recommender systems become …
recommender systems. As the application scenarios of recommender systems become …
User interest modeling and collaborative filtering algorithms application in English personalized learning resource recommendation
W ** - Soft Computing, 2023 - Springer
In order to solve the problem that the current traditional English classroom teaching in large
classes has higher teaching efficiency, but it is difficult to take care of every student, and it is …
classes has higher teaching efficiency, but it is difficult to take care of every student, and it is …