Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 162521, 8 pages
http://dx.doi.org/10.1155/2014/162521
Research Article

A Robust Collaborative Filtering Approach Based on User Relationships for Recommendation Systems

1School of Software Engineering, Chongqing University, Chongqing 400044, China
2Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing 400044, China
3School of Engineering, University of Portsmouth, Portsmouth PO1 3AH, UK

Received 12 August 2013; Revised 10 December 2013; Accepted 30 December 2013; Published 19 February 2014

Academic Editor: Xing-Gang Yan

Copyright © 2014 Min Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [7 citations]

The following is the list of published articles that have cited the current article.

  • Deepti Mishra, and Saroj Hiranwal, “Analysis & implementation of item based collaboration filtering using K-Medoid,” 2014 International Conference on Advances in Engineering & Technology Research (ICAETR - 2014), pp. 1–5, . View at Publisher · View at Google Scholar
  • Ruoxuan Wei, and Hong Shen, “An Improved Collaborative Filtering Recommendation Algorithm against Shilling Attacks,” 2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT), pp. 330–335, . View at Publisher · View at Google Scholar
  • Wenyu Zhang, Shixiong Zhang, Shuai Zhang, and Dejian Yu, “A novel method for MCDM and evaluation of manufacturing services using collaborative filtering and IVIF theory,” Journal of Algorithms and Computational Technology, vol. 10, no. 1, pp. 40–51, 2016. View at Publisher · View at Google Scholar
  • Monika Singh, “Scalability and sparsity issues in recommender datasets: a survey,” Knowledge and Information Systems, 2018. View at Publisher · View at Google Scholar
  • Mingdan Si, and Qingshan Li, “Shilling attacks against collaborative recommender systems: a review,” Artificial Intelligence Review, 2018. View at Publisher · View at Google Scholar
  • Qin Yang, “A robust recommended system based on attack detection,” Concurrency Computation , 2018. View at Publisher · View at Google Scholar
  • Xiang Li, and Zhijian Wang, “Multidimensional context-aware recommendation algorithm towards intelligent distribution of cold chain logistics,” Journal of Intelligent and Fuzzy Systems, vol. 35, no. 1, pp. 171–185, 2018. View at Publisher · View at Google Scholar