Trust-based collaborative filtering algorithm in social network

Xinxin Chen, Yu Guo, Yang Yang, Zhenqiang Mi
{"title":"Trust-based collaborative filtering algorithm in social network","authors":"Xinxin Chen, Yu Guo, Yang Yang, Zhenqiang Mi","doi":"10.1109/CITS.2016.7546412","DOIUrl":null,"url":null,"abstract":"In order to improve the accuracy of recommendation algorithm in social network applications, a new recommendation method based on traditional collaborative filtering recommendation algorithm, which called Trust-based Collaborative Filtering, is proposed and verified in this paper. Firstly, we analyze users' behaviors and relationships in social network, and propose a trust calculation method based on Dijkstra's algorithm. Secondly, we integrate users' trust information into the collaborative filtering algorithm to recommend in social network. Finally, we choose Flixster dataset to validate the proposed model and use the Mean Absolute Error (MAE) as the evaluation metric. Experiment results show that Trust-based CF significantly improves the recommendation quality in social network.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITS.2016.7546412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

In order to improve the accuracy of recommendation algorithm in social network applications, a new recommendation method based on traditional collaborative filtering recommendation algorithm, which called Trust-based Collaborative Filtering, is proposed and verified in this paper. Firstly, we analyze users' behaviors and relationships in social network, and propose a trust calculation method based on Dijkstra's algorithm. Secondly, we integrate users' trust information into the collaborative filtering algorithm to recommend in social network. Finally, we choose Flixster dataset to validate the proposed model and use the Mean Absolute Error (MAE) as the evaluation metric. Experiment results show that Trust-based CF significantly improves the recommendation quality in social network.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信任的社交网络协同过滤算法
为了提高推荐算法在社交网络应用中的准确率,本文在传统协同过滤推荐算法的基础上提出了一种新的推荐方法——基于信任的协同过滤。首先,我们分析了社交网络中用户的行为和关系,提出了一种基于Dijkstra算法的信任计算方法。其次,将用户信任信息整合到协同过滤算法中进行社交网络推荐。最后,我们选择Flixster数据集来验证所提出的模型,并使用平均绝对误差(MAE)作为评估指标。实验结果表明,基于信任的CF显著提高了社交网络中的推荐质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Recursive construction of quasi-cyclic cycle LDPC codes based on replacement products Design and realization of IMA/DIMA system management based on avionics switched network Mining co-location patterns with spatial distribution characteristics Multilayer perceptron for modulation recognition cognitive radio system Joint hierarchical modulation and network coding for asymmetric data transmission in wireless cooperative communication
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1