A Model for Preserving Privacy in Recommendation Systems

被引：0
|
作者：
Troiano, Luigi [1 ]
Diaz, Irene [2 ]
机构：
[1] Univ Sannio, Benevento, Italy
[2] Univ Oviedo, Oviedo, Spain
来源：
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, PT II | 2014年 / 443卷
关键词：
Recommendation System; Privacy; Prominence Index; Frequent Item Sets;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The problem of preserving privacy in recommendation systems is faced in this work. The approach presented reduces the study of privacy threats to the study of frequent property set obtained from the characteristics of the objects the recommendation system provides to a target user. This study is made by defining a prominence index for each item and by using efficient methods to explore the lattice of item characteristics.
引用
收藏
页码：56 / 65
页数：10
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