计算机科学 ›› 2016, Vol. 43 ›› Issue (9): 107-110.doi: 10.11896/j.issn.1002-137X.2016.09.020
• 2015 年第三届CCF 大数据学术会议 • 上一篇 下一篇
胡亚慧,杨莎,刘晶,余伟,李石君,王俊,方其庆
HU Ya-hui, YANG Sha, LIU Jing, YU Wei, LI Shi-jun, WANG Jun and FANG Qi-qing
摘要： 如何从海量的数据中将不同的商品在恰当的时间、合理的位置推荐给适当的人(或人群)是当前面临的主要挑战。考虑到不同国家不同区域的人(或人群)在宗教信仰、职业、教育程度等方面有着不同的文化背景差异,以及大数据环境下商品推荐常常面临数据稀疏和冷启动等问题,从签到数据中抽取出目标用户所在的地理位置,根据该位置的文化背景特点筛选出与目标用户有相似或相同的文化背景的人群；再根据每个商品适宜购买的最佳合理时间和间隔购买时间选出恰当的商品,运用因子分解机的思想建立用户-区域-时间-商品因子分解模型。大量真实数据集上的实验表明该模型能够在数据量大、高稀疏的数据环境下进行商品推荐,验证了该方法的可行性、有效性和高效性。
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