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Neural Collaborative Preference Learning With Pairwise Comparisons

文献类型：期刊论文

作者Li, Zhaopeng7,8,9; Xu, Qianqian6; Jiang, Yangbangyan7,8; Ma, Ke4,5; Cao, Xiaochun3,4,7; Huang, Qingming1,2,5,6
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2021
卷号23页码:1977-1989
关键词Recommender system collaborative ranking neural networks preference ranking
ISSN号1520-9210
DOI10.1109/TMM.2020.3006373
英文摘要Collaborative Ranking (CR), as an effective recommendation framework, has attracted increasing attention in recent years. Most CR methods simply adopt the inner product between user/item embeddings as the rating score function, with an assumption that the interacted items are preferred to non-interacted ones. However, such fixed score functions and assumptions might not be sufficient to capture the real preference ranking list from the complicated interactions in real-world data. To alleviate this issue, we develop a novel collaborative ranking framework that learns an arbitrary utility function for item ranking with user preference concerned. In the core of our framework, a neural network is employed to model the utility function for personalized ranking with the strength of its nonlinearity. On top of this, we further adopt a pairwise ranking loss for user-item pairs to preserve the preference order of items for users. Besides, such a utility function enables us to generate the final top-K preference list in a much easier way. Finally, extensive experiments on four real-world datasets show the validity of our proposed method.
资助项目National Key R&D Program of China[2018AAA0102003] ; National Natural Science Foundation of China[61620106009] ; National Natural Science Foundation of China[U1636214] ; National Natural Science Foundation of China[61931008] ; National Natural Science Foundation of China[61836002] ; National Natural Science Foundation of China[61971016] ; National Natural Science Foundation of China[U1936208] ; National Natural Science Foundation of China[61672514] ; National Natural Science Foundation of China[61976202] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-SYS013] ; Beijing Education Committee Cooperation Beijing Natural Science Foundation[KZ201910005007] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB28000000] ; Beijing Natural Science Foundation[4182079] ; Youth Innovation Promotion Association CAS
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:000724477100005
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/18151]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Huang, Qingming
作者单位1.Peng Cheng Lab, Shenzhen 518055, Peoples R China
2.Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management BDKM, Beijing 101408, Peoples R China
3.Chinese Acad Sci, Inst Informat Engn, Key Lab Informat Secur, Beijing 100093, Peoples R China
4.Peng Cheng Lab, Artificial Intelligence Res Ctr, Shenzhen 518055, Peoples R China
5.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
7.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100049, Peoples R China
8.Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur SKLOIS, Beijing 100093, Peoples R China
9.Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur, SKLOIS, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Li, Zhaopeng,Xu, Qianqian,Jiang, Yangbangyan,et al. Neural Collaborative Preference Learning With Pairwise Comparisons[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2021,23:1977-1989.
APA Li, Zhaopeng,Xu, Qianqian,Jiang, Yangbangyan,Ma, Ke,Cao, Xiaochun,&Huang, Qingming.(2021).Neural Collaborative Preference Learning With Pairwise Comparisons.IEEE TRANSACTIONS ON MULTIMEDIA,23,1977-1989.
MLA Li, Zhaopeng,et al."Neural Collaborative Preference Learning With Pairwise Comparisons".IEEE TRANSACTIONS ON MULTIMEDIA 23(2021):1977-1989.

入库方式： OAI收割

来源：计算技术研究所

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