Personalized ranking with pairwise Factorization Machines
文献类型：期刊论文
| 作者 | Guo, Weiyu1,2; Wu, Shu1 ; Wang, Liang1; Tan, Tieniu1
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2016-11-19 |
| 卷号 | 214期号:null页码:191-200 |
| 关键词 | Personalized Ranking Adaptive Sampling Pairwise Learning |
| DOI | 10.1016/j.neucom.2016.05.074 |
| 文献子类 | Article |
| 英文摘要 | Pairwise learning is a vital technique for personalized ranking with implicit feedback. Given the assumption that each user is more interested in items which have been previously selected by the user than the remaining ones, pairwise learning algorithms can well learn users' preference, from not only the observed user feedbacks but also the underlying interactions between users and items. However, a mass of training instances are randomly derived according to such assumption, which makes the learning procedure often converge slowly and even result in poor predictive models. In addition, the cold start problem often perplexes pairwise learning methods, since most of traditional methods in personalized ranking only take explicit ratings or implicit feedbacks into consideration. For dealing with the above issues, this work proposes a novel personalized ranking model which incorporates implicit feedback with content information by making use of Factorization Machines. For efficiently estimating the parameters of the proposed model, we develop an adaptive sampler to draw informative training instances based on content information of users and items. The experimental results show that our adaptive item sampler indeed can speed up our model, and our model outperforms advanced methods in personalized ranking. (C) 2016 Elsevier B.V. All rights reserved. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000386741300020 |
| 资助机构 | National Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61403390 ; U1435221) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12313]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Wu, Shu |
| 作者单位 | 1.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guo, Weiyu,Wu, Shu,Wang, Liang,et al. Personalized ranking with pairwise Factorization Machines[J]. NEUROCOMPUTING,2016,214(null):191-200. |
| APA | Guo, Weiyu,Wu, Shu,Wang, Liang,&Tan, Tieniu.(2016).Personalized ranking with pairwise Factorization Machines.NEUROCOMPUTING,214(null),191-200. |
| MLA | Guo, Weiyu,et al."Personalized ranking with pairwise Factorization Machines".NEUROCOMPUTING 214.null(2016):191-200. |
入库方式： OAI收割
来源：自动化研究所
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