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工程科学与技术:2015,47(6):131-138
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基于概念格和随机游走的社交网朋友推荐算法
(1.武汉大学软件工程国家重点实验室;2.武汉大学)
A Friends Recommendation Algorithm Based on Formal Concept Analysis and Random Walk in Social Network
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投稿时间:2015-03-26    修订日期:2015-08-21
中文摘要: 在社交网络朋友推荐上,现有方法通过用户注册的共同属性或者用户共同邻居来对用户进行朋友推荐,由于缺乏对用户之间关系的深入的挖掘,推荐精度不高。本文采用概念格从数据中挖掘知识,利用用户特征属性和社交网络图建立概念格,提出了弹性随机游走方法SRWR,并在此基础上用概念格知识指导随机游走,提出了融合概念格和随机游走的FCASRWR方法,度量了用户之间的相似性,算法最终根据相似度进行朋友推荐。实验采用Facebook的真实数据集,采用AUC和精确度评价指标,实验结果表明了该方法比目前主流的方法在指标上有较大提高,验证了方法的准确性。
中文关键词: 社交网络  概念格  随机游走  朋友推荐
Abstract:In order to provide personal friends recommendation service,social networking sites often recommended friends through registered users’ property or common user neighbor friends. Because of the lack of deep mining to user relationships, the recommendation accuracy was not high. In this paper, formal concept analysis was leveraged to acquire knowledge in data. Two concept lattices were built from the user feature attributes and social networking diagram. The random walk method SRWR was proposed and then the FCASRWR method was put forward with the guidance of concept lattice .The FCASRWR method measured the similarity between users, and recommends friends according to the similarity algorithm to users. The Experiments used Facebook's real datasets , and the experimental result showed that the proposed method had a better performance and proved the accuracy of the method.
文章编号:201500274     中图分类号:    文献标志码:
基金项目:网络数据复杂性度量与计算基础理论研究 2014CB340401
Author NameAffiliationE-mail
Li Hong Tao  wsjlht@163.com 
何克清   
王健   
彭珍连   
田刚   
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引用文本:
李宏涛,何克清,王健,彭珍连,田刚.基于概念格和随机游走的社交网朋友推荐算法[J].工程科学与技术,2015,47(6):131-138.
Li Hong Tao,何克清,王健,彭珍连,田刚.A Friends Recommendation Algorithm Based on Formal Concept Analysis and Random Walk in Social Network[J].Advanced Engineering Sciences,2015,47(6):131-138.