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	Purchase Prediction via Machine Learning in Mobile Commerce
	Lv, Chao ; Feng, Yansong ; Zhao, Dongyan
	2016
关键词	Purchase prediction Machine learning RECOMMENDER SYSTEMS MATRIX FACTORIZATION
英文摘要	In this paper, we propose a machine learning approach to solve the purchase prediction task launched by the Alibaba Group. In detail, we treat this task as a binary classification problem and explore five kinds of features to learn potential model of the influence of historical behaviors. These features include user quality, item quality, category quality, user-item interaction and user-category interaction. Due to the nature of mobile platform, time factor and spacial factor are considered specially. Our approach ranks the 26th place among 7186 teams in this task.; National Natural Science Foundation of China [61272344, 61370116]; CPCI-S(ISTP); 506-513; 10102
语种	英语
出处	5th International Conference on Natural Language Processing and Chinese Computing (NLPCC) / 24th International Conference on Computer Processing of Oriental Languages (ICCPOL)
DOI标识	10.1007/978-3-319-50496-4_43
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470121]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Lv, Chao,Feng, Yansong,Zhao, Dongyan. Purchase Prediction via Machine Learning in Mobile Commerce. 2016-01-01.

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