A review on the dynamics of social recommender systems

被引:0
|
作者
Shokeen J. [1 ]
Rana C. [1 ]
机构
[1] Department of Computer Science and Engineering, University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak, Haryana
关键词
Cold-start; Dynamics; Recommender system; Social networks; Social recommender system;
D O I
10.1504/IJWET.2018.095184
中图分类号
学科分类号
摘要
With the excessive growth of data over internet, it has become difficult to select relevant items and information. Recommender systems are the essential tools to handle the information overload problem and suggesting relevant items to users. On the other hand, a growing explosion of social networking sites in recent years is influencing different aspects of our life. For many years, recommender systems and social networks have been considered as separate areas. But with time, researchers comprehended the significance of combining them to generate improved results. The integration of social networks into recommender system is called social recommender system. In this paper, we investigate different dynamics of social recommender systems that play a major role in generating effective recommendations. Each dynamic individually enhances the quality of social recommender system but the fusion of these dynamics can produce accurate and most striking recommendations. This paper also discusses the relevant research areas in this field. Copyright © 2018 Inderscience Enterprises Ltd.
引用
收藏
页码:255 / 276
页数:21
相关论文
共 50 条
  • [1] Systematic Review on Online Social Media Recommender Systems
    Sibanda, Elias Mbongeni
    Zuva, Tranos
    SOFTWARE ENGINEERING PERSPECTIVES IN SYSTEMS, VOL. 1, 2022, 501 : 675 - 684
  • [2] Social Relations and Methods in Recommender Systems: A Systematic Review
    Medel, Diego
    Gonzalez-Gonzalez, Carina
    Aciar, Silvana, V
    INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2022, 7 (04): : 7 - 17
  • [3] Social Media Recommender Systems: Review and Open Research Issues
    Anandhan, Anitha
    Shuib, Liyana
    Ismail, Maizatul Akmar
    Mujtaba, Ghulam
    IEEE ACCESS, 2018, 6 : 15608 - 15628
  • [4] Recommender Systems: A Review
    LeBlanc, Patrick M.
    Banks, David
    Fu, Linhui
    Li, Mingyan
    Tang, Zhengyu
    Wu, Qiuyi
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2024, 119 (545) : 773 - 785
  • [5] A Review on Recommender Systems
    Mansur, Farhin
    Patel, Vibha
    Patel, Mihir
    2017 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION, EMBEDDED AND COMMUNICATION SYSTEMS (ICIIECS), 2017,
  • [6] Improving social recommender systems
    Arazy, Ofer
    Kumar, Nanda
    Shapira, Bracha
    IT Professional, 2009, 11 (04) : 38 - 44
  • [7] Research on social recommender systems
    Meng, Xiang-Wu
    Liu, Shu-Dong
    Zhang, Yu-Jie
    Hu, Xun
    Ruan Jian Xue Bao/Journal of Software, 2015, 26 (06): : 1356 - 1372
  • [8] Social Tagging in Recommender Systems
    Arabi, Hossein
    Balakrishnan, Vimala
    2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND TECHNOLOGY (ICCST), 2014,
  • [9] Workshop on Social Recommender Systems
    Guy, Ido
    Chen, Li
    Zhou, Michelle X.
    IUI 2010, 2010, : 433 - 434
  • [10] Tutorial on Social Recommender Systems
    Guy, Ido
    WWW'14 COMPANION: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON WORLD WIDE WEB, 2014, : 195 - 195