Recommendation in evolving online networks
文献类型：期刊论文
| 作者 | Hu, Xiao1; Zeng, An2; Shang, Ming-Sheng3
|
| 刊名 | EUROPEAN PHYSICAL JOURNAL B
 |
| 出版日期 | 2016-02-17 |
| 卷号 | 89期号:2页码:7 |
| ISSN号 | 1434-6028 |
| DOI | 10.1140/epjb/e2016-60509-9 |
| 通讯作者 | Zeng, A (reprint author), Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China. |
| 英文摘要 | Recommender system is an effective tool to find the most relevant information for online users. By analyzing the historical selection records of users, recommender system predicts the most likely future links in the user-item network and accordingly constructs a personalized recommendation list for each user. So far, the recommendation process is mostly investigated in static user-item networks. In this paper, we propose a model which allows us to examine the performance of the state-of-the-art recommendation algorithms in evolving networks. We find that the recommendation accuracy in general decreases with time if the evolution of the online network fully depends on the recommendation. Interestingly, some randomness in users' choice can significantly improve the long-term accuracy of the recommendation algorithm. When a hybrid recommendation algorithm is applied, we find that the optimal parameter gradually shifts towards the diversity-favoring recommendation algorithm, indicating that recommendation diversity is essential to keep a high long-term recommendation accuracy. Finally, we confirm our conclusions by studying the recommendation on networks with the real evolution data. |
| 资助项目 | National Natural Science Foundation of China[61370150] ; National Natural Science Foundation of China[61433014] ; Sci & Tech Research Project of Chongqing[cstc2015jcyjB0244] ; Youth Scholars Program of Beijing Normal University[2014NT38] |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| 出版者 | SPRINGER |
| WOS记录号 | WOS:000375218200002 |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/2477]  |
| 专题 | 大数据挖掘及应用中心 |
| 通讯作者 | Zeng, An |
| 作者单位 | 1.Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Web Sci Ctr, Chengdu 610054, Peoples R China 2.Beijing Normal Univ, Sch Syst Sci, Beijing 100875, Peoples R China 3.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Xiao,Zeng, An,Shang, Ming-Sheng. Recommendation in evolving online networks[J]. EUROPEAN PHYSICAL JOURNAL B,2016,89(2):7. |
| APA | Hu, Xiao,Zeng, An,&Shang, Ming-Sheng.(2016).Recommendation in evolving online networks.EUROPEAN PHYSICAL JOURNAL B,89(2),7. |
| MLA | Hu, Xiao,et al."Recommendation in evolving online networks".EUROPEAN PHYSICAL JOURNAL B 89.2(2016):7. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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