中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
LOTMAP: learning to optimize top-N recommendation with mean average precision

文献类型:期刊论文

作者Yang Yehui1; Zhang Wensheng1; Xie Yuan1; Zhu Limin1; Tan Yuanhua2
刊名Innovative Computing, Information and Control Express Lettersv
出版日期2014-12
卷号8期号:12页码:3299-3306
关键词Top-n Recommendation Collaborative Filtering Optimize Matrix Factorization Mean Average Precision
英文摘要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.
源URL[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.

入库方式: OAI收割

来源:自动化研究所

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