Multiobjective Personalized Recommendation Algorithm Using Extreme Point Guided Evolutionary Computation
Recommender systems suggest items to users based on their potential interests, and they are important to alleviate the search and selection pressures induced by the increasing item information. Classical recommender systems mainly focus on the accuracy of recommendation. However, with the increase o...
Saved in:
| Main Authors: | Qiuzhen Lin, Xiaozhou Wang, Bishan Hu, Lijia Ma, Fei Chen, Jianqiang Li, Carlos A. Coello Coello |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/1716352 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Evolutionary Search with Multiple Utopian Reference Points in Decomposition-Based Multiobjective Optimization
by: Wu Lin, et al.
Published: (2019-01-01) -
A Constrained Solution Update Strategy for Multiobjective Evolutionary Algorithm Based on Decomposition
by: Yuchao Su, et al.
Published: (2019-01-01) -
Decomposition-Based Multiobjective Evolutionary Optimization with Adaptive Multiple Gaussian Process Models
by: Xunfeng Wu, et al.
Published: (2020-01-01) -
Knee Point-Guided Multiobjective Optimization Algorithm for Microgrid Dynamic Energy Management
by: Wenhua Li, et al.
Published: (2020-01-01) -
Personalized-Template-Guided Intelligent Evolutionary Algorithm
by: Dongni Hu, et al.
Published: (2025-08-01)