计算机工程 ›› 2019, Vol. 45 ›› Issue (4): 175-180.doi: 10.19678/j.issn.1000-3428.0051647

• 人工智能及识别技术 • 上一篇    下一篇

基于关联规则与相似度的社交好友推荐算法

向程冠,熊世桓,王东,熊伟程   

  1. 贵州师范学院 数学与大数据学院,贵阳 550018
  • 收稿日期:2018-05-24 出版日期:2019-04-15 发布日期:2019-04-15
  • 作者简介:向程冠(1981—),男,副教授、硕士,主研方向为推荐系统、大数据技术、数据挖掘;熊世桓、王东,教授;熊伟程,副教授、硕士。
  • 基金项目:

    贵州省教育厅青年科技人才成长项目(黔教KY字[2017]205);贵州省科学技术基金计划项目(黔科合基础[2016]1115);2016年度贵州省科技平台及人才团队专项资金(20165609);2016年贵州省普通高等学校工程研究中心专项资金(黔教合KY字[2016]015)。

Social Friend Recommendation Algorithm Based on Association Rules and Similarity

XIANG Chengguan,XIONG Shihuan,WANG Dong,XIONG Weicheng   

  1. School of Mathematics and Big Data,Guizhou Education University,Guiyang 550018,China
  • Received:2018-05-24 Online:2019-04-15 Published:2019-04-15

摘要:

针对现有社交好友推荐算法只关注“人”忽略“事”的问题,提出一种基于关联规则与相似度的推荐算法。通过对用户每天发布的信息进行相似度计算,将相似度达到给定阈值的信息视为一条交易记录,把发布的信息视为交易项,信息库视为交易数据库,计算出二阶候选项集,推荐支持数最高的前N项信息的发布者为好友。实验结果表明,与基于关联规则与标签的好友推荐算法相比,该算法具有较高的准确率。

关键词: 好友推荐算法, 关联规则, 社交平台, 相似度, 交易数据库

Abstract:

Aiming at the problem that the existing social friend recommendation algorithm only focuses on people and ignores things,a recommendation algorithm based on association rules and similarity is proposed.By calculating the similarity of the information released by the user every day,the information with the similarity reaching the given threshold is regarded as a transaction record,the published information is regarded as the transaction item,the information database is regarded as the transaction database,and the second-order candidate set is calculated.It is recommended that the publisher who supports the top N items of the highest number of friends be friends.Experimental results show that compared with the friend recommendation algorithm based on association rules and labels,this algorithm has higher accuracy.

Key words: friend recommendation algorithm, association rules, social platform, similarity, transaction database

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