摘要
提出了一种基于关联规则的社交网络好友推荐算法,在进行好友推荐时,考虑现实社交活动中"志趣相投"的好友常常会关注相同的人和事,网络社交中的好友也常常会关注相同的"人"和"事",将"关注"看成一条交易记录,把关注的用户看成交易项,所有交易项的集合看成交易数据库,生成二阶候选项集,并按支持数降序排序,推荐前N个用户作为好友。以新浪微博993 950条用户关注数据及552 600条微博关注数据作为实验的对象,实验结果表明,算法具有良好的性能,可实现较高的召回率与准确率。
A social network friends recommendation algorithm based on association rules is proposed.Considering that in our daily life,the congenial friends always pay close attention to the persons and things of similar purpose and interests,so do cyber good friends,we take＆quot;focus＆quot;as a trade record,the focusing users as the trade terms and the set of all the trade terms as the trade da-ta,then the set of second order candidates is produced and we descend the number of supporters.The former N users are recom-mended as good friends.Taking 993 950 users’focus data and 552 600 focus data in Sina microblog as the experiment objects,we reach the conclusion that the proposed algorithm has good performance and can achieve the higher recalling rate and precision rate.
出处
《中国科技论文》
CAS
北大核心
2014年第1期87-91,共5页
China Sciencepaper
基金
贵州省优秀科技教育人才省长专项资金项目(黔省专合字(2012)82号)
关键词
关联规则
网络社交
新浪微博
召回率
association rules
social network
Sina microlog
recalling rate
