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A New Framework for Increasing User Engagement in Mobile Applications Using Machine Learning Techniques

机译:使用机器学习技术提高用户参与的新框架

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摘要

In this paper, it is proposed to build a new framework which anticipates mobile user status and behavior characteristics with the aim of increasing user engagement and provide stickiness in mobile applications (iOS-Android) by using machine learning techniques. Motivation of this study is based on the idea of collecting data from users by non-survey methods because data collection from surveys may mislead the system model according to the literature researches on user experience. User behavior includes forecasting next usage time of the user, user motivation type, user mastery level and current context of the user. In order to find relevant patterns, usage data is obtained from pilot mobile applications at first and then they are processed according to the chosen machine learning algorithm.
机译:在本文中,提出建立一个新的框架,该框架预测移动用户状态和行为特征,目的是通过使用机器学习技术来增加用户参与并在移动应用程序(iOS-Android)中提供粘性。 本研究的动机是基于非调查方法从用户收集数据的想法,因为从调查的数据收集可能会根据用户体验的文献研究误导系统模型。 用户行为包括预测用户的下一个使用时间,用户动机类型,用户掌握级别和用户的当前上下文。 为了找到相关模式,首先从导频移动应用获得使用数据,然后根据所选择的机器学习算法处理它们。

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