Research on social recommendation algorithm based on fuzzy subjective trust

References

• Arora, A., & Taneja, A. (2021). Research issues, innovation and associated approaches for recommendation on social networks. International Journal of Performability Engineering, 17(12), 1027–1036. https://doi.org/10.23940/ijpe.21.12.p7.10271036
   Google Scholar
• Bushra, A., & Yousef, K. (2020). The recommender system: A survey. International Journal of Advanced Intelligence Paradigms, 15(3), 229–251. https://doi.org/10.1504/IJAIP.2020.105815
   Google Scholar
• Chen, T., Zhu, Q., Zhou, M., & Wang, S. (2016). A trust-based recommendation algorithm in social network environment. Journal of Software, 28(3), 721–731. https://doi.org/10.13328/j.cnki.jos.005159
   Google Scholar
• Dionisis, M., & Costas, V. (2020). Improving collaborative filtering's rating prediction coverage in sparse datasets by exploiting the 'friend of a friend' concept. International Journal of Big Data Intelligence, 7(1), 47–57. https://doi.org/10.1504/IJBDI.2020.106178
   Google Scholar
• Gan, Zaobin, Zeng, Can, Ma, Yao, Lu, Hongwei, (2015). C2C e-commerce trust algorithm based on trust network. Journal of Software, 26(8), 1946–1959. https://doi.org/10.13328/j.cnki.jos.004690
   Google Scholar
• Gan, Z. B., Zeng, C., Li, K., & Han J.-J. (2012). Construction and optimization of trust network in e-commerce environment. Chinese Journal of Computers, 35(1), 27–37. https://doi.org/10.3724/SP.J.1016.2012.00027
   Google Scholar
• Guo, L., Ma, J., & Chen, Z. (2013). A socialized recommendation algorithm based on the strength of trust relationship. Journal of Computer Research and Development, 50(9), 1805–1813. CNKI:SUN:JFYZ.0.2013-09-003
   Google Scholar
• Guo, L., Yu, W.-S., & Wu, Q.-S. (2021). Simulation of joint matrix factorization recommendation algorithm integrating trust relationship. Computer Simulation, 38(2), 378–382. https://doi.org/10.3969/j.issn.1006-9348.2021.02.081
   Google Scholar
• Hu, Y., Li, H., & Shi, W. (2017). Socialized recommendation algorithm combining score and trust relationship. Journal of Computer Applications, 37(3), 791–795. https://doi.org/10.11772/j.issn.1001-9081.2017.03.791
   Google Scholar
• Huang, Liwei, Jiang, Bitao, Lv, Shouye, et al. (2018). Survey on deep learning based recommender systems. Chinese Journal of Computers, 41(7), 1619–1647. https://doi.org/10.11897/SP.J.1016.2018.01619
   Google Scholar
• International Telecommunications Union. (2000). ITU_T Recommendation X.509 ISO/IEC 9594-8: Information Technology-Open Systems Interconnection-The Directory Public-key and Attribute Certificate Frameworks[S]. ITU-T,2000.
   Google Scholar
• Ive, A. D. S. T., & Tatiane, N. R. (2021). FACF: Fuzzy areas-based collaborative filtering for point-of-interest recommendation. International Journal of Computational Science and Engineering, 24(1), 27–41. https://doi.org/10.1504/IJCSE.2021.113636
   Web of Science ®Google Scholar
• Jia, R., Li, R., & Gao, M. (2019). Study on data sparsity in social network-based recommender system. International Journal of Computational Science and Engineering, 20(1), 15–20. https://doi.org/10.1504/IJCSE.2019.103245
   Web of Science ®Google Scholar
• Ju, C., Gu, Q., & Li, J. (2021). Research on application recommendation method integrating user social relationship and trust relationship. Journal of Systems Science and Mathematical Sciences, 41(12), 144–161. https://doi.org/10.12341/jssms14101
   Google Scholar
• Li, Tianyuan, Su, Xin, Liu, Wei, Liang, Wei, Hsieh, Meng-Yen, Chen, Zhuhui, Liu, XuChong, Zhang, Hong, et al. (2022). Memory-augmented meta-learning on meta-path for fast adaptation cold-start recommendation. Connection Science, 34(1), 301–318. https://doi.org/10.1080/09540091.2021.1996537
   Web of Science ®Google Scholar
• Li, Y., Chen, L., Shi, C., & Lan, X. (2018). Enhanced collaborative filtering algorithm adopting trust network. Application Research of Computers, 35(1), 117–120. https://doi.org/10.3969/j.issn.1001-3695.2018.01.024
   Google Scholar
• Liu, N., Lu, Y., Tang, X.-J., Li, M.-X., & Wang, C. (2020). Improved user-based collaborative filtering algorithm with topic model and time tag. International Journal of Computational Science and Engineering, 22(2-3), 181–189. https://doi.org/10.1504/IJCSE.2020.107340
   Web of Science ®Google Scholar
• Lv, C.-S. (2020). Anti-Attack social recommendation algorithm based on multiple implicit trust relationship. Operations Research and Management Science, 29(1), 69–77. CNKI:SUN:YCGL.0.2020-01-010
   Google Scholar
• Meeker, M. (2017). Internet trends 2017 reports [EB/OL].2017-12-10. http://www.kpcb.com/internet-trends
   Google Scholar
• Meng, H., Gao, C., Wang, S., Zhang, L.-L., & Liu, N. (2020). User clustering collaborative filtering recommendation algorithm combined with trust relationship. Computer Systems & Applications, 29(8), 224–229. https://doi.org/10.15888/j.cnki.csa.007561
   Google Scholar
• Nassira, C., Ilyes, C., Souham, M., Badreddine, C., Didier, S., Mohamed, B., & Amel, Z. (2020). SCOL: Similarity and credibility-based approach for opinion leaders detection in collaborative filtering-based recommender systems. International Journal of Reasoning-Based Intelligent Systems, 12(1), 34–50. https://doi.org/10.1504/IJRIS.2020.105006
   Google Scholar
• Shen, J., Zhou, T., & Chen, L. (2020). Collaborative filtering-based recommendation system for big data. International Journal of Computational Science and Engineering, 21(2), 219–225. https://doi.org/10.1504/IJCSE.2020.105727
   Web of Science ®Google Scholar
• Sheng, L., & Song, Y. (2022). An improved social recommendation model based on implicit trust information. Journal of Chinese Computer Systems, 43(2), 306–311. https://doi.org/10.20009/j.cnki.21-1106/TP.2020-0870
   Google Scholar
• Tang, X., & Sun, F. (2015). Research on social media friends recommendation based on complex trust network. Information Studies Theory & Practice, 38(11), 96–102. https://doi.org/10.16353/j.cnki.1000-7490.2015.11.019
   Google Scholar
• Tong, X.-R., Jiang, X.-X., Wang, Y.-J., & Zhang, N. (2017). Research on the systems. Journal of Chinese Computer Systems, 38(1), 92–98. CNKI:SUN:XXWX.0.2017-01-018
   Google Scholar
• Wang, H., Yu, X., Zhao, J., & Zheng, Y. (2019). Detecting sparse rating spammer for accurate ranking of online recommendation. International Journal of Computational Science and Engineering, 19(1), 121–131. https://doi.org/10.1504/IJCSE.2019.099646
   Web of Science ®Google Scholar
• Wu, H., Bian, Y., Zhao, Z., & Ma, R.-M. (2014). Collaborative filtering algorithm based on trust. Computer Systems & Applications, 24(7), 131–135. https://doi.org/10.3969/j.issn.1003-3254.2014.07.025
   Google Scholar
• Wu, H., & Jiang, H. (2019). Collaborative filtering recommendation based on potential social trust model. Computer Engineering and Applications, 55(20), 114–121. https://doi.org/10.3778/j.issn.1002-8331.1807-0043
   Google Scholar
• Yu, D., Chen, R., & Chen, J. (2020). Video recommendation algorithm based on knowledge graph and collaborative filtering. International Journal of Performability Engineering, 16(12), 1933–1940. https://doi.org/10.23940/ijpe.20.12.p9.19331940
   Google Scholar
• Yu, S., Xiong, L., & Wang, L. (2020). A social recommendation method based on user preference and trust-trust relationship. Journal of Chinese Computer Systems, 41(12), 2529–2535. 1000-1220041:012<2529:YZRHYH>2.0.TX;2-E
   Google Scholar
• Zhang, S. (2006). Research on Fuzzy Trust Model and national PKI system. Sichuan: Chengdu. Southwest Jiaotong University. https://doi.org/10.7666/d.y884767
   Google Scholar
• Zhang, T. (2019). Research on collaborative filtering recommendation algorithm based on social network. International Journal of Internet Manufacturing and Services, 6(4), 343–356. https://doi.org/10.1504/IJIMS.2019.103874
   Google Scholar
• Zhang, X., & Huang, G. (2020). Trust-based shilling attacks user detection algorithm. Computer Applications and Software, 37(11), 286–291. https://doi.org/10.3969/j.issn.1000-386x.2020.11.046
   Google Scholar
• Zhou, Ya, Chai, Wang, Han, Junyang, Zhang, Guoliang (2018). Recommendation algorithm based on user comprehensive trust degree and community trust propagation. Computer Engineering, 44(12), 294–300. CNKI:SUN:JSJC.0.2018-12-049
   Google Scholar
• Zhu, A. (2020). Personalised recommendation algorithm for social network based on two-dimensional correlation. International Journal of Autonomous and Adaptive Communications Systems, 13(2), 195–209. https://doi.org/10.1504/IJAACS.2020.109807
   Google Scholar
• Zou, Y., Wu, H., Jiang, Y., & Zhao, Y. (2020). Recommendation algorithm based on filling method and multi-weight similarity. Application Research of Computers, 37(12), 3578–3581. https://doi.org/10.19734/j.issn.1001-3695.2019.09.0541
   Google Scholar