标题：Commodity Recommendation for Users Based on E-commerce Data
作者：Yang, Fei; Han, Xudong; Lang, Jiying; Lu, Weigang; Liu, Lei; Zhang, Lei; Pan, Jingchang
作者机构：[Yang, Fei; Han, Xudong] Shandong Univ, Sch Mech Elect & Informat Engn, Room 512,180 Wenhua Xilu, Weihai 264209, Peoples R China.; [Lang, Jiying; Pa 更多
会议名称：2nd International Conference on Big Data Research (ICBDR)
会议日期：OCT 27-29, 2018
来源：PROCEEDINGS OF THE 2018 2ND INTERNATIONAL CONFERENCE ON BIG DATA RESEARCH (ICBDR 2018)
关键词：Mobile terminal; Consumption prediction; GBDT; Distributed platform
摘要：With the popularity of mobile devices and the development of e-commerce, more and more people choose to buy items in the mobile terminal. Therefore the mobile terminal commodity recommendation services and commodity recommendation algorithms are more and more important. Aim at this problem, this paper conducts a study of predicting the user's purchase behavior based on the online distribution platform and the desensitization data sets provided by the Chinese largest electricity platform Alibaba. Based on the GBDT (Gradient Boosting Decision Tree) model, by using ODPS (Open Data Processing Service) and Python to simultaneously implement machine learning and training online and offline respectively, and combining with the user behavior sequence recorded over a period of time, the user purchase behavior at a later time will be properly predicted.