[1]陈思憬,骆冰清,孙知信.基于混合好友路径信任度的社交好友推荐算法[J].计算机技术与发展,2018,28(02):74-77.[doi:10.3969/j.issn.1673-629X.2018.02.017]
 CHEN Si-jing,LUO Bing-qing,SUN Zhixin.Social Friend Recommendation Algorithm Based on Trust of Paths between Mixed Friends[J].,2018,28(02):74-77.[doi:10.3969/j.issn.1673-629X.2018.02.017]
点击复制

基于混合好友路径信任度的社交好友推荐算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年02期
页码:
74-77
栏目:
出版日期:
2018-02-10

文章信息/Info

Title:
Social Friend Recommendation Algorithm Based on Trust of Paths between Mixed Friends
文章编号:
1673-629X(2018)02-0074-04
作者:
陈思憬1 骆冰清2 孙知信1
1.南京邮电大学 物联网学院,江苏 南京 210000;2.南京邮电大学 通信与信息工程学院,江苏 南京 210000)
Author(s):
CHEN Si-jing1LUO Bing-qing2SUN Zhi-xin1
1.School of Internet of Things,Nanjing University of Posts and Telecommunications,Nanjing 210000,China;
2.School of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210000,China
关键词:
社交网络三度影响力好友路径信任度好友推荐
Keywords:
social mediathree degrees of influencefriend pathtrustfriend recommendation
分类号:
TP391
DOI:
10.3969/j.issn.1673-629X.2018.02.017
文献标志码:
A
摘要:
为了解决以往好友信任度计算准确性不足的问题,提出依据三度以内好友路径信任度的好友推荐算法。与传统的依据好友信任度的好友推荐算法相比,传统的信任度算法仅仅考虑二度好友路径对用户之间好友信任度的影响,而忽略了三度好友路径的作用。根据三度影响力理论,在以往依据二度好友路径信任度推荐算法的基础上,引入三度好友路径信任度对好友推荐效果的影响能得到更准确的信任度计算效果。计算用户间的混合好友路径信任度,并依据混合好友路径信任度进行好友推荐,其好友推荐效果更准确。实验结果表明,比起没有引入三度好友路径的信任度算法,引入三度好友路径信任度的混合好友路径信任度算法其 F1-measure 评价指标增加了 3 到 4 个百分点,能有效提高好友信任度计算的准确性以及好友推荐的有效性。
Abstract:
To address the previous inaccurate calculation of trust level between friends,we propose a friend recommendation algorithm according to trust of paths between friends within three degrees.Traditional trust-based friend recommendation algorithm only considered the influence of two-degree path on the trust between users and ignored the function of three-degree path of trust.Based on the three degrees of influence rule and the trust of two-degree friend path,this algorithm introduces the influence of three-degree trust path on friend recommen-
dation,calculating the trust between mixed friends and performing friend recommendation in accordance with the trust of path between mixed friends.Compared to the case without introducing the new algorithm,the experiment shows that there is a three to four percentage increase of recommendation in the evaluation index of F1-measure for the social friend recommendation algorithm based on trust level of path between mixed friends,which can improve the accuracy of calculating trust between friends and the effectiveness in friend recommendation.

相似文献/References:

[1]李桃陶,周斌,王忠振. 基于社交网络的图数据挖掘应用研究[J].计算机技术与发展,2014,24(10):6.
 LI Tao-tao,ZHOU Bin,WANG Zhong-zhen. Research on Graph Data Mining Application Based on Social Network[J].,2014,24(02):6.
[2]张付霞,蒋朝惠. 基于DSNPP算法的社交网络隐私保护方法[J].计算机技术与发展,2015,25(08):152.
 ZHANG Fu-xia,JIANG Chao-hui. Privacy-preserving Approach in Social Networks Based on DSNPP Algorithm[J].,2015,25(02):152.
[3]李梦洁,邵曦.基于文本属性的微博用户相似度研究[J].计算机技术与发展,2018,28(05):17.[doi:10.3969/j.issn.1673-629X.2018.05.005]
 LI Meng-jie,SHAO Xi. Research on Micro-blog User Similarity Based on Text Similarity[J].,2018,28(02):17.[doi:10.3969/j.issn.1673-629X.2018.05.005]
[4]房旋[],陈升波[],宫婧[][],等. 基于社交影响力的推荐算法[J].计算机技术与发展,2016,26(06):31.
 FANG Xuan[],CHEN Sheng-bo[],GONG Jing[][],et al. A Recommendation Algorithm Based on Social Influence[J].,2016,26(02):31.
[5]余莎莎[],王友国[],朱亮[]. 基于SIR社交网络中商业谣言传播研究[J].计算机技术与发展,2016,26(11):195.
 YU Sha-sha[],WANG You-guo[],ZHU Liang[]. Research on Online Business Rumors Transmission Based on an Improved SIR Model[J].,2016,26(02):195.
[6]余莎莎[],王友国[],朱亮[]. 基于网络博弈论的谣言扩散建模研究[J].计算机技术与发展,2017,27(04):6.
 YU Sha-sha[],WANG You-guo[],ZHU Liang[]. Investigation on Rumor Diffusion Modeling with Network Game Theory[J].,2017,27(02):6.
[7]付明明,余莎莎,应志领. 在线社交网络的双谣言模型研究[J].计算机技术与发展,2017,27(09):53.
 FU Ming-ming,YU Sha-sha,YING Zhi-ling. Research on Double Rumor Model in Online Social Network[J].,2017,27(02):53.
[8]李旗旗,徐敏. 社交网络中的链路预测方法改进[J].计算机技术与发展,2017,27(11):37.
 LI Qi-qi,XU Min. Improvement of Link Prediction Method in Social Networks[J].,2017,27(02):37.
[9]王冰玉,吴振宇,沈苏彬.一种社交网络的增量社区检测算法及实现优化[J].计算机技术与发展,2018,28(10):64.[doi:10.3969/ j. issn.1673-629X.2018.10.013]
 WANG Bing-yu,WU Zhen-yu,SHEN Su-bin.An Incremental Community Detection Algorithm for Social Networks and Its Optimization[J].,2018,28(02):64.[doi:10.3969/ j. issn.1673-629X.2018.10.013]
[10]初晓宇,高守玮.基于优先连接和用户属性的链路预测算法研究[J].计算机技术与发展,2019,29(11):17.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 004]
 CHU Xiao-yu,GAO Shou-wei.Research on Link Prediction Algorithm Based on Professional Attachment and User Attributes[J].,2019,29(02):17.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 004]

更新日期/Last Update: 2018-03-28