LOTMAP: learning to optimize top-N recommendation with mean average precision
Yang Yehui1; Zhang Wensheng1; Xie Yuan1; Zhu Limin1; Tan Yuanhua2
2014-12
发表期刊Innovative Computing, Information and Control Express Lettersv
卷号8期号:12页码:3299-3306
摘要People tend to pay attention to the top few items given by recommendation system,
it's crucial to ensure the precision and personalization at the top of recommendation list.
In this paper, we propose a ranking-oriented Collaborative Filtering (CF) algorithm LOTMAP,
which aims to optimize the top-N recommendation by directly maximizing Mean Average Precision (MAP). As the relevance between users and items are not clarified in rating datasets, we also introduce a new method that judges the relevance through the explicit rating scores. Experiments on real world datasets show that our algorithm is effective, and outperforms the state-of-the-art CF baselines.
关键词Top-n Recommendation Collaborative Filtering Optimize Matrix Factorization Mean Average Precision
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11502
专题精密感知与控制研究中心_精密感知与控制
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.$Karamay Hongyou Software CO., LTD
推荐引用方式
GB/T 7714
Yang Yehui,Zhang Wensheng,Xie Yuan,et al. LOTMAP: learning to optimize top-N recommendation with mean average precision[J]. Innovative Computing, Information and Control Express Lettersv,2014,8(12):3299-3306.
APA Yang Yehui,Zhang Wensheng,Xie Yuan,Zhu Limin,&Tan Yuanhua.(2014).LOTMAP: learning to optimize top-N recommendation with mean average precision.Innovative Computing, Information and Control Express Lettersv,8(12),3299-3306.
MLA Yang Yehui,et al."LOTMAP: learning to optimize top-N recommendation with mean average precision".Innovative Computing, Information and Control Express Lettersv 8.12(2014):3299-3306.
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