中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
  5. 多媒体计算与图形学团队
Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information Networks

文献类型：期刊论文

作者Sang, Lei1,2; Xu, Min2; Qian, Shengsheng3; Martin, Matt4; Li, Peter4; Wu, Xindong1,5
刊名IEEE TRANSACTIONS ON MULTIMEDIA
出版日期2021
卷号23页码:2019-2032
关键词Semantics Collaboration YouTube Australia Visualization Context modeling Video recommendation context-dependent propagating Heterogeneous Information Network (HIN) Network embedding
ISSN号1520-9210
DOI10.1109/TMM.2020.3007330
通讯作者Xu, Min(Min.Xu@uts.edu.au)
英文摘要With the emergence of online social networks (OSNs), video recommendation has come to play a crucial role in mitigating the semantic gap between users and videos. Conventional approaches to video recommendation primarily focus on exploiting content features or simple user-video interactions to model the users' preferences. Although these methods have achieved promising results, they fail to model the complex video context interdependency, which is obscure/hidden in heterogeneous auxiliary data from OSNs. In this paper, we study the problem of video recommendation in Heterogeneous Information Networks (HINs) due to its excellence in characterizing heterogeneous and complex context information. We propose a Context-Dependent Propagating Recommendation network (CDPRec) to obtain accurate video embedding and capture global context cues among videos in HINs. The CDPRec can iteratively propagate the contexts of a video along links in a graph-structured HIN and explore multiple types of dependencies among the surrounding video nodes. Then, each video is represented as the composition of the multimodal content feature and global dependency structure information using an attention network. The learned video embedding with sequential based recommendation are jointly optimized for the final rating prediction. Experimental results on real-world YouTube video recommendation scenarios demonstrate the effectiveness of the proposed methods compared with strong baselines.
资助项目National Key Research and Development Program of China[2016YFB1000901] ; China Scholarship Council (CSC) ; National Natural Science Foundation of China[91746209] ; Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of theMinistry of Education of China[IRT17R32]
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:000668875100014
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China ; China Scholarship Council (CSC) ; National Natural Science Foundation of China ; Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of theMinistry of Education of China
源URL[http://ir.ia.ac.cn/handle/173211/45231]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Xu, Min
作者单位1.Hefei Univ Technol, Key Lab Knowledge Engn Big Data, Minist Educ, Hefei 230009, Peoples R China
2.Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
4.INTERACT Technol, Sydney, NSW 2000, Australia
5.Mininglamp Acad Sci, Mininglamp Technol, Beijing 100084, Peoples R China
推荐引用方式
GB/T 7714		 Sang, Lei,Xu, Min,Qian, Shengsheng,et al. Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information Networks[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2021,23:2019-2032.
APA Sang, Lei,Xu, Min,Qian, Shengsheng,Martin, Matt,Li, Peter,&Wu, Xindong.(2021).Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information Networks.IEEE TRANSACTIONS ON MULTIMEDIA,23,2019-2032.
MLA Sang, Lei,et al."Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information Networks".IEEE TRANSACTIONS ON MULTIMEDIA 23(2021):2019-2032.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。