Modeling recommender systems via weighted bipartite network-Reference-Cited by-同舟云学术

Modeling recommender systems via weighted bipartite network

Published:2016-08-03 Issue:14 Volume:29 Page:e3895
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat.: Pract. Exper.

Author:

Xia Jianxun¹²,Wu Fei¹,Xiong Zenggang²,Qiu Meikang²³,Xie Changsheng¹

Affiliation:

1. School of Computer Sci. and Tech.; Huazhong University of Science and Technology; Wuhan 430074 Hubei China

2. School of Computer and Information Science; Hubei Engineering University; Xiaogan 432000 Hubei China

3. Computer Science Department; Pace University; New York NY 10038 USA

Funder

National Natural Science Foundation of China

National Natural Science Foundation of Hubei Province

Fundamental Research Funds for the Central Universities

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cpe.3895/fullpdf

Reference44 articles.

1. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions;Adomavicius;IEEE Transactions on Knowledge and Data Engineering,2005

2. Recent advances in personal recommender systems;Liu;International Journal of Information and Systems Sciences,2009

3. Proactive user-centric secure data scheme using attribute-based semantic access controls for mobile clouds in financial industry;Qiu;Future Generation Computer Systems,2016

4. Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing;Gai;Journal of Network and Computer Applications,2016

5. Using collaborative filtering to weave an information tapestry;Goldberg;Communications of the ACM,1992

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic bipartite network model based on structure and preference features;Knowledge and Information Systems;2024-04-06

2. Toward a BCI-Based Personalized Recommender System Using Deep Learning;2022 IEEE 8th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS);2022-05

3. Alleviating the data sparsity problem of recommender systems by clustering nodes in bipartite networks;Expert Systems with Applications;2020-07

4. Personalized recommendation via network-based inference with time;Physica A: Statistical Mechanics and its Applications;2020-07

5. A potential naphthyl-thiazole-based organic dye and a ditopic chromogenic probe for CN− and Fe3+ with molecular logic functions;New Journal of Chemistry;2020