[1]杜淑颖,丁世飞.基于六度分割理论的社交好友推荐算法研究[J].南京理工大学学报(自然科学版),2019,43(04):468-473.[doi:10.14177/j.cnki.32-1397n.2019.43.04.013]
 Du Shuying,Ding Shifei.Research on recommendation algorithm of social friendsbased on six-degree segmentation theory[J].Journal of Nanjing University of Science and Technology,2019,43(04):468-473.[doi:10.14177/j.cnki.32-1397n.2019.43.04.013]
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基于六度分割理论的社交好友推荐算法研究()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
43卷
期数:
2019年04期
页码:
468-473
栏目:
出版日期:
2019-08-24

文章信息/Info

Title:
Research on recommendation algorithm of social friendsbased on six-degree segmentation theory
文章编号:
1005-9830(2019)04-0468-06
作者:
杜淑颖12丁世飞1
1.中国矿业大学 计算机科学与技术学院,江苏 徐州 221116; 2.徐州生物工程职业技术学院 财经信息系,江苏 徐州 221000
Author(s):
Du Shuying12Ding Shifei1
1.School of Computer Science and Technology,China University of Mining and Technology,Xuzhou 221116,China; 2.Department of Finance Information,Xuzhou Vocational College of Bioengineering,Xuzhou 221000,China
关键词:
好友推荐 六度分割算法 好友分级 社交网络
Keywords:
friends recommendation six degree segmentation algorithm friend ratings social network
分类号:
TP391
DOI:
10.14177/j.cnki.32-1397n.2019.43.04.013
摘要:
为了更好地拓宽用户社交圈并且通过新朋友获取更多的信息资源,好友推荐成为社交网络最为青睐的对象。该文在分析现有朋友推荐算法的基础上,提出基于六度分割理论的社交好友推荐算法。首先,该方法以好友分级思想为基础,根据用户的历史行为对用户进行评级,将评级相似的用户合并为一个群组,以减少进行大规模好友推荐时的时间代价; 其次,考虑用户之间的共同关注关系,以及用户与好友交流的时间差额,计算用户与好友之间的相似程度。采用新浪微博数据集验证算法的性能,最终实验证明:该算法准确性和召回率都得到了提升。
Abstract:
In order to better broaden the user’s social circle and get more information resources through new friends,friends recommendation to become the most popular target of social networking. Based on the analysis of the existing friend recommendation algorithm,this paper puts forward the social friend recommendation algorithm based on the theory of six-degree segmentation. Specifically,first,the method is based on the idea of friend rating,according to the user’s historical behavior to rate users,similar rating users into a group,to reduce the time cost of large-scale friend recommendation; Secondly,considering the relationship of common concern between users and the time difference between users and friends,the similarity between users and friends is calculated. The performance of the Sina Weibo data set verification algorithm was used,and the final experiment proves that the accuracy and recall rate of the algorithm is improved.

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备注/Memo

备注/Memo:
收稿日期:2019-05-24 修回日期:2019-06-18
基金项目:国家自然科学基金(61672522).
作者简介:杜淑颖(1981-),女,副教授,主要研究方向:机器学习、网络通信,E-mail:du3477@139.com; 通讯作者:丁世飞(1963-),男,博士,教授,主要研究方向:人工智能、机器学习、数据挖掘等,E-mail:dingsf@cumt.edu.cn。
引文格式:杜淑颖,丁世飞. 基于六度分割理论的社交好友推荐算法研究[J]. 南京理工大学学报,2019,43(4):468-473.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2019-09-30