CASIA OpenIR  > 综合信息系统研究中心
Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach
Zhang, Haidong1; Ni, Wancheng1; Li, Xin2; Yang, Yiping1
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
2018-02-01
Volume48Issue:2Pages:177-194
SubtypeArticle
AbstractRecommender systems are widely used for suggesting books, education materials, and products to users by exploring their behaviors. In reality, users' preferences often change over time, leading to studies on time-dependent recommender systems. However, most existing approaches that deal with time information remain primitive. In this paper, we extend existing methods and propose a hidden semi-Markov model to track the change of users' interests. Particularly, this model allows for capturing the different durations of user stays in a (latent) interest state, which can better model the heterogeneity of user interests and focuses. We derive an expectation maximization algorithm to estimate the parameters of the framework and predict users' actions. Experiments on three real-world datasets show that our model significantly outperforms the state-of-the-art time-dependent and static benchmark methods. Further analyses of the experiment results indicate that the performance improvement is related to the heterogeneity of state durations and the drift of user interests in the dataset.
KeywordCollaborative Filtering (Cf) Hidden Semi-markov Model (Hsmm) Recommender System Time-dependent Recommendation
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TSMC.2016.2599705
WOS KeywordSOCIAL NETWORK ; E-COMMERCE ; SYSTEMS ; DYNAMICS ; CHAINS ; WEB
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61174190 ; GuangDong Natural Science Foundation(2015A030313876) ; CityU SRG(7004287) ; Shenzhen Research Institute, City University of Hong Kong ; 71572169)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000422795800002
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21939
Collection综合信息系统研究中心
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Haidong,Ni, Wancheng,Li, Xin,et al. Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2018,48(2):177-194.
APA Zhang, Haidong,Ni, Wancheng,Li, Xin,&Yang, Yiping.(2018).Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,48(2),177-194.
MLA Zhang, Haidong,et al."Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 48.2(2018):177-194.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang, Haidong]'s Articles
[Ni, Wancheng]'s Articles
[Li, Xin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang, Haidong]'s Articles
[Ni, Wancheng]'s Articles
[Li, Xin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang, Haidong]'s Articles
[Ni, Wancheng]'s Articles
[Li, Xin]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.