Social personalized ranking recommendation algorithm by trust

机译：信任的社会个性化排名推荐算法

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The problem with previous studies of social personalized ranking (SPR) algorithms is that they simply integrated the user's social network information into their model, without taking into account the transmission of social trust networks between users. To solve this problem, a new social personalized ranking recommendation algorithm (TrustSPR) based on ListRank algorithm and the newest TrustMF algorithm is proposed, which aims to improve the performance of personalized ranking recommendation algorithm. Experimental results on a real-world dataset showed that the TrustSPR algorithm outperformed state-of-the-art SPR approachs over different evaluation metrics, and that the TrustSPR algorithm possesses good expansibility.

机译：先前对社会个性化排名（SPR）算法的研究存在的问题是，它们只是将用户的社交网络信息集成到其模型中，而没有考虑用户之间的社交信任网络的传输。针对这一问题，提出了一种基于ListRank算法和最新TrustMF算法的社会化个性化排名推荐算法（TrustSPR），旨在提高个性化排名推荐算法的性能。在真实数据集上的实验结果表明，在不同的评估指标上，TrustSPR算法的性能优于最新的SPR方法，并且TrustSPR算法具有良好的可扩展性。

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《2017 International Conference on Security, Pattern Analysis, and Cybernetics》|2017年|273-277|共5页
会议地点 Shenzhen(CN)
作者
Gai Li; You-fen Chen; Zhi-qiang Zhang; Jiang-hong Zhong; Wei-hua Ou;
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作者单位

Department of Electronics and Information Engineering, Shunde Polytechnic, Foshan 528300, China;

Department of Electronics and Information Engineering, Shunde Polytechnic, Foshan 528300, China;

Department of Electronics and Information Engineering, Shunde Polytechnic, Foshan 528300, China;

Department of Electronics and Information Engineering, Shunde Polytechnic, Foshan 528300, China;

School of Big Data and Computer Science, Guizhou Normal University;

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原文格式 PDF
正文语种 eng
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关键词
Prediction algorithms; Collaboration; Filtering; Social network services; Measurement; Security; Pattern analysis;

机译：预测算法;协作;过滤;社交网络服务;度量;安全性;模式分析;;

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专利

1. Personalized recommendation algorithm for social networks based on comprehensive trust [J] . Zhang Zhijun, Xu Gongwen, Zhang Pengfei, Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies . 2017,第3期

机译：基于全面信任的社交网络的个性化推荐算法
2. Towards generating scalable personalized recommendations: Integrating social trust, social bias, and geo-spatial clustering [J] . Divyaa L. R., Pervin Nargis Decision support systems . 2019,第JULa期

机译：致力于生成可扩展的个性化建议：整合社会信任，社会偏见和地理空间聚类
3. Towards generating scalable personalized recommendations: Integrating social trust, social bias, and geo-spatial clustering [J] . Divyaa L. R., Pervin Nargis Decision support systems . 2019,第Jula期

机译：生成可扩展个性化建议：整合社会信任，社会偏见和地理空间聚类
4. Social personalized ranking recommendation algorithm by trust [C] . Gai Li, You-fen Chen, Zhi-qiang Zhang, International Conference on Security, Pattern Analysis, and Cybernetics . 2017

机译：信任的社会个性化排名推荐算法
5. Machine-Learned Ranking Algorithms for E-commerce Search and Recommendation Applications [D] . Goswami, Anjan. 2018

机译：机器学习的电子商务搜索和推荐应用排名算法
6. UISTD: A Trust-Aware Model for Diverse Item Personalization in Social Sensing with Lower Privacy Intrusion [O] . Hongchen Wu, Mingyang Li, Huaxiang Zhang 2018

机译：UISTD：具有较低隐私入侵的社交感知中多种项目个性化的信任感知模型
7. Social Influence from Personalized Recommendations to Trusting Beliefs of Websites: Intermediate Role of Social Presence [O] . Li, Yanan, Wang, Yong 2013

机译：从个性化推荐对网站信任的社会影响：社会存在的中介作用

Social personalized ranking recommendation algorithm by trust

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