A hybrid recommendation system with many-objective evolutionary algorithm
文献类型：期刊论文
| 作者 | Cai, Xingjuan1; Hu, Zhaoming1; Zhao, Peng1; Zhang, WenSheng3 ; Chen, Jinjun2
|
| 刊名 | EXPERT SYSTEMS WITH APPLICATIONS
 |
| 出版日期 | 2020-11-30 |
| 卷号 | 159页码:10 |
| ISSN号 | 0957-4174 |
| 关键词 | Recommendation systems Many-objective optimization Hybrid recommender algorithm Collaborative filtering |
| DOI | 10.1016/j.eswa.2020.113648 |
| 通讯作者 | Cai, Xingjuan(xingjuancai@163.com) |
| 英文摘要 | Recommendation system (RS) is a technology that provides accurate recommendations to users. However, it is not comprehensive to only consider the accuracy of the recommendation because users have different requirements. To improve the comprehensive performance, this paper presents a hybrid recommendation model based on many-objective optimization, which can simultaneously optimize the accuracy, diversity, novelty and coverage of recommendation. This model enhances the robustness of recommendations by mixing three different basic recommendation technologies. Additionally, we solve it with many-objective evolutionary algorithm (MaOEA) and test it extensively. Experimental results demonstrate the effectiveness of the presented model, which can provide the recommendations with more and novel items on the basis of accurate and diverse. (C) 2020 Elsevier Ltd. All rights reserved. |
| WOS关键词 | SWARM OPTIMIZATION ALGORITHM ; BAT ALGORITHM |
| 资助项目 | National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61663028] ; Natural Science Foundation of Shanxi Province[201801D121127] ; Key R&D program of Shanxi Province (High Technology)[201903D121119] |
| WOS研究方向 | Computer Science ; Engineering ; Operations Research & Management Science |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000583204100034 |
| 资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Shanxi Province ; Key R&D program of Shanxi Province (High Technology) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/41803]  |
| 专题 | 精密感知与控制研究中心_人工智能与机器学习 |
| 通讯作者 | Cai, Xingjuan |
| 作者单位 | 1.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan, Shanxi, Peoples R China 2.Univ Technol Sydney, Sydney, NSW, Australia 3.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cai, Xingjuan,Hu, Zhaoming,Zhao, Peng,et al. A hybrid recommendation system with many-objective evolutionary algorithm[J]. EXPERT SYSTEMS WITH APPLICATIONS,2020,159:10. |
| APA | Cai, Xingjuan,Hu, Zhaoming,Zhao, Peng,Zhang, WenSheng,&Chen, Jinjun.(2020).A hybrid recommendation system with many-objective evolutionary algorithm.EXPERT SYSTEMS WITH APPLICATIONS,159,10. |
| MLA | Cai, Xingjuan,et al."A hybrid recommendation system with many-objective evolutionary algorithm".EXPERT SYSTEMS WITH APPLICATIONS 159(2020):10. |
入库方式： OAI收割
来源：自动化研究所
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