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机构地区:[1]广东工业大学自动化学院,广东广州510006
出 处:《无线互联科技》2017年第15期21-23,共3页Wireless Internet Technology
摘 要:针对开放移动互联网下难以识别和跟踪潜在用户,无法提供更具个性化服务的状况,文章在传统决策树分类器的基础上,提取用户基础数据特征,引入感知模型分析处理用户行为数据,提出一种基于决策树的移动互联网用户付费分类预测方法。该方法强化用户感知对付费行为的影响,利用决策树建模进行分类并最终作出付费预测,根据模型结果探究付费影响因素,从运营者角度思考如何提高用户的付费意愿。In view of the situation taht due to open mobile network is difficult to identify and track potential users, which cannot provide more targeted services, based on traditional decision tree classifier, this paper extracts feature of user data and introduces the perception model to analyze users' behavior data processing, a classification method for mobile Internet users' pay classification based on decision tree is proposed.This method strengthens the influence of user perception on cost behavior, and uses decision tree modeling to classify and makes final payment prediction, to think how to improve the users' willingness to pay from the operator point of view.
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