A Recommendation Algorithm Based on Dynamic User Preference and Service Quality

被引:10
|
作者
Zhang, Yanmei [1 ]
Qian, Ya [1 ]
Wang, Yan [2 ]
机构
[1] Cent Univ Finance & Econ, Informat Sch, Beijing 100081, Peoples R China
[2] Macquarie Univ, Dept Comp, Sydney, NSW 2109, Australia
基金
中国国家自然科学基金;
关键词
service composition; service recommendation; user preference; LDA; quality of services;
D O I
10.1109/ICWS.2018.00019
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In the field of service computing, user preferences and service quality may change with time, environment and other factors. A recommendation algorithm that considers both the dynamic characteristics of users and the dynamic quality of services (QoS) is proposed in this paper. On the one hand, this algorithm uses a kind of temporal LDA (Latent Dirichlet Allocation) model to mine dynamic user preferences. On the other hand, it considers the dynamic changes of QoS and focuses on the latest QoS. The service recommendation list is then generated for the user based on dynamic user preferences and dynamic QoS. Experimental results on a real world dataset show that the proposed algorithm outperforms some classic algorithms and the state-of-the-art algorithms in terms of accuracy, recall and diversity.
引用
收藏
页码:91 / 98
页数:8
相关论文
共 50 条
  • [21] Collaborative Filtering Recommendation Algorithm Based on label of tourist spots and User Preference
    Zhou, Ya
    Hu, Cailin
    Xiong, Han
    Li, Ling
    Wei, Xiafei
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MACHINERY, ELECTRONICS AND CONTROL SIMULATION (MECS 2017), 2017, 138 : 44 - 51
  • [22] Recommendation algorithm based on item quality and user rating preferences
    Yuan Guan
    Shimin Cai
    Mingsheng Shang
    Frontiers of Computer Science, 2014, 8 : 289 - 297
  • [23] Recommendation algorithm based on item quality and user rating preferences
    Guan, Yuan
    Cai, Shimin
    Shang, Mingsheng
    FRONTIERS OF COMPUTER SCIENCE, 2014, 8 (02) : 289 - 297
  • [24] A collaborative filtering recommendation algorithm based on user preferences on service properties
    Mu, Wenzhong
    Meng, Fanchao
    Chu, Dianhui
    PROCEEDINGS 2014 INTERNATIONAL CONFERENCE ON SERVICE SCIENCES (ICSS 2014), 2014, : 43 - 46
  • [25] A Service Recommendation System Based on Dynamic User Groups and Reinforcement Learning
    Zhang, En
    Ma, Wenming
    Zhang, Jinkai
    Xia, Xuchen
    ELECTRONICS, 2023, 12 (24)
  • [26] Hotel Recommendation based on User Preference Analysis
    Zhang, Kai
    Wang, Keqiang
    Wang, Xiaoling
    Jin, Cheqing
    Zhou, Aoying
    2015 13TH IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS (ICDEW), 2015, : 134 - 138
  • [27] A Service Recommendation Algorithm Based on Modeling of Dynamic and Diverse Demands
    Zhang, Yanmei
    Lei, Tingpei
    Qin, Zhiguang
    INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, 2018, 15 (01) : 47 - 70
  • [28] A New-user cold-starting recommendation algorithm based on normalization of preference
    Liu, Ji
    Deng, Guishi
    2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 9170 - 9173
  • [29] A Recommendation Algorithm For Collaborative Denoising Auto-Encoders Based On User Preference Diffusion
    Wang, Xiu
    Liu, Xuejun
    Xu, Xinyan
    PROCEEDINGS OF 2017 8TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2017), 2017, : 447 - 450
  • [30] An O2O Service Recommendation Algorithm Based on User context and Trust Service
    Han, Hongfang
    Gao, Ang
    Xue, Xiao
    Ren, Jianji
    Ma, Yongqiang
    2016 IEEE TRUSTCOM/BIGDATASE/ISPA, 2016, : 1904 - 1909