Unison-CF: A multiple-component, adaptive collaborative filtering system

被引:0
|
作者
Vozalis, M [1 ]
Margaritis, KG [1 ]
机构
[1] Univ Macedonia, Dept Appl Informat, Parallel Distributed Proc Lab, Thessaloniki 54006, Greece
关键词
collaborative filtering; memory-based filtering; adaptation; personalization; prediction; recommender systems;
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
In this paper we present the Unison-CF algorithm, which provides an efficient way to combine multiple collaborative filtering approaches, drawing advantages from each one of them. Each collaborative filtering approach is treated as a separate component, allowing the Unison-CF algorithm to be easily extended. We evaluate the Unison-CF algorithm by applying it on three existing filtering approaches: User-based Filtering, Item-based Filtering and Hybrid-CF. Adaptation is utilized and evaluated as part of the filtering approaches combination. Our experiments show that the Unison-CF algorithm generates promising results in improving the accuracy and coverage of the existing filtering algorithms.
引用
收藏
页码:255 / 264
页数:10
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