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Cited by 90Privacy-Preserving Technologies in DataRecommender Systems and TechniquesPrivacy, Security, and Data Protection

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Improved collaborative filtering recommendation algorithm based on differential privacy protection

Yin, Chunyong, Shi, Lingfeng, Sun, Ruxia, Wang, Jin·2020·The Journal of Supercomputing
DOI 10.1007/s11227-019-02751-7
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Crossref · 10.1007/s11227-019-02751-7

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Citations

Cites

Research works printed but not linked: 30

  1. Tang L, Jiang Y, Li L et al (2015) Personalized recommendation via parameter-free contextual bandits. In: International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, pp 323–332 · DOI
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  8. Li J, Tang B, Cercone N (2004) Applying association rules for interesting recommendations using rule templates. In: Advances in Knowledge Discovery and Data Mining. Springer, Berlin, pp 166–170 · DOI
  9. Yin C, Feng L, Ma L (2016) An improved Hoeffding-ID data-stream classification algorithm. J Supercomput 72(7):2670–2681 · DOI
  10. Mooney RJ, Bennett PN, Roy L (2017) Book recommending using text categorization with extracted information. In: Recommender Systems Papers from Workshop 2017, pp 49–54
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  16. Shen Y, Jin H (2014) Privacy-preserving personalized recommendation: an instance-based approach via differential privacy. In: IEEE International Conference on Data Mining 2014, pp 540–549 · DOI
  17. Jin H, Jin H (2016) EpicRec: towards practical differentially private framework for personalized recommendation. In: ACM Sigsac Conference on Computer and Communications Security. ACM, pp 180–191
  18. Huang J, Qi J, Xu Y, Chen J (2015) A privacy-enhancing model for location-based personalized recommendations. Distrib Parallel Databases 33(2):253–276 · DOI
  19. Ahmed KW, Mouri IJ, Zaman R et al (2016) A privacy preserving personalized group recommendation framework. In: International Conference on Advanced Computing. IEEE, pp 594–598 · DOI
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  26. Yin C, Xia L, Zhang S, Sun R, Wang J (2017) Improved clustering algorithm based on high-speed network data stream. Soft Comput 22(13):4185–4195 · DOI
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  29. Yin C, Zhang S, Yin Z, Wang J (2017) Anomaly detection model based on data stream clustering. Cluster Comput 2017:1–10
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Metadata

Authors
Yin, C., Shi, L., Sun, R., & Wang, J.
Affiliations
  • Nanjing University of Information Science and Technology (CN)
  • Changsha University of Science and Technology (CN)
Corresponding author
Wang, Jin
ORCID
Venue
The Journal of Supercomputing
Publisher
Springer Science and Business Media LLC
Published
2019-01-08
Volume
76
Issue
7
Pages
5161-5174
ISSN
  • 0920-8542 (ISSN-L)
  • 1573-0484
DOI
10.1007/s11227-019-02751-7
OpenAlex
W3046301713
Cited by
90
References
1
Citations by year
2026: 4 · 2025: 10 · 2024: 11 · 2023: 12 · 2022: 25 · 2021: 16 · 2020: 7 · 2019: 5
FWCI
6.11
Type
journal article
Language
en
Open access
closed
Licence
Locations
The Journal of Supercomputing (publishedVersion)
Funders
National Natural Science Foundation of China (61772282, 61772454, 61811530332)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
Keywords
collaborative filtering, differential privacy, privacy-preserving recommendation, personalized recommendation, time factor, user privacy protection, recommendation accuracy

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