[1]方楷强,王靖.采用矩阵分解模型的托攻击防御算法[J].华侨大学学报(自然科学版),2018,39(1):109-114.[doi:10.11830/ISSN.1000-5013.201510059]
　FANG Kaiqiang,WANG Jing.Shilling Attack Defense Algorithm Using Matrix Factorization Model[J].Journal of Huaqiao University(Natural Science),2018,39(1):109-114.[doi:10.11830/ISSN.1000-5013.201510059]
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采用矩阵分解模型的托攻击防御算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第1期
页码:
109-114
栏目:
出版日期:
2018-01-17

文章信息/Info

Title:
Shilling Attack Defense Algorithm Using Matrix Factorization Model
文章编号:
1000-5013(2018)01-0109-06
作者:
方楷强;  王靖
华侨大学 计算机科学与技术学院, 福建 厦门 361021
Author(s):
FANG Kaiqiang;  WANG Jing
College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China
关键词:
推荐系统;  托攻击;  矩阵分解;  信任度权值矩阵
Keywords:
recommender systems;  shilling attack;  matrix factorization;  trust weight matrix
分类号:
TP311
DOI:
10.11830/ISSN.1000-5013.201510059
文献标志码:
A
摘要:
提出一种基于矩阵分解模型的托攻击防御算法框架.首先,利用托攻击检测技术,度量用户是托用户的概率,并以此构造信任度权值矩阵;然后,将此权值矩阵引入到矩阵分解模型,以降低托用户攻击行为的影响;最后,通过求解新模型实现对用户评分的预测.实验结果表明:这类算法与其他协同过滤算法相比较,能够更有效地抵御托攻击.
Abstract:
A shilling attack defense algorithm framework based on matrix factorization model is proposed. Firstly, using the technology of shilling attack detection, measuring the probability of the shilling and constructing a trust weight matrix. Then, the weight matrix is introduced into the matrix factorization model to reduce the influence of the shilling attack. Finally, by solving the new model to realize the user values prediction. Experimental results show that this algorithms are more effective in resisting the shilling attacks compared to other collaborative filtering algorithms.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-10-29
通信作者: 王靖(1981-),男,教授,博士,主要从事模式识别、推荐系统的研究.E-mail:wroaring@hqu.edu.cn.
基金项目: 国家自然科学基金资助项目(61370006); 福建省自然科学基金资助项目(2014J01237); 福建省教育厅科技项目(JA12006); 福建省高等学校新世纪优秀人才支持计划(2012FJ-NCET-ZR01); 华侨大学中青年教师科技创新资助计划(ZQN-PY116)
更新日期/Last Update: 2018-01-20