LOTMAP: learning to optimize top-N recommendation with mean average precision

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	LOTMAP: learning to optimize top-N recommendation with mean average precision
	Yang Yehui1 ; Zhang Wensheng1 ; Xie Yuan1 ; Zhu Limin1 ; Tan Yuanhua 2
刊名	Innovative Computing, Information and Control Express Lettersv
	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.
内容类型	期刊论文
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.