期刊
MULTIMEDIA TOOLS AND APPLICATIONS
卷 74, 期 9, 页码 3053-3076出版社
SPRINGER
DOI: 10.1007/s11042-013-1768-2
关键词
Recommender systems; Hybrid; Algorithms; RMSE; Optimization
类别
资金
- Ghent University
- Hercules Foundation
- Flemish Government - Department EWI
Massive availability of multimedia content has given rise to numerous recommendation algorithms that tackle the associated information overload problem. Because of their growing popularity, selecting the best one is becoming an overload problem in itself. Hybrid algorithms, combining multiple individual algorithms, offer a solution, but often require manual configuration and power only a few individual recommendation algorithms. In this work, we regard the problem of configuring hybrid recommenders as an optimization problem that can be trained in an offline context. Focusing on the switching and weighted hybridization techniques, we compare and evaluate the resulting performance boosts for hybrid configurations of up to 10 individual algorithms. Results showed significant improvement and robustness for the weighted hybridization strategy which seems promising for future self-adapting, user-specific hybrid recommender systems.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据