Owing the continuous enrichment of mobile application resources, mobile applications carry almost all user behaviors and preferences. The analysis of user behavior regarding mobile terminals has become an important research direction. The frequency with which users click on mobile applications reflects their preferences to a certain extent. In this study, we propose a mobile application click-frequency prediction model based on heterogeneous information network representation. This model first constructs a heterogeneous information network between users’ mobile devices and mobile applications. To generate a meaningful sequence of network-embedded nodes, we perform a random walk on a specified meta-path. Finally, the prediction of users’ mobile application click frequency is completed using representation fusion and matrix factorization. Experiments show that our method outperforms other baseline methods in terms of the mean absolute error and root mean square error. Therefore, the application of a heterogeneous information network representation method to the prediction model is effective. This study is significant to the behavior research of mobile terminal users.

中文翻译：

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HEPre：基于异构信息网络嵌入的应用点击频率预测

由于移动应用资源的不断丰富，移动应用承载了几乎所有的用户行为和偏好。移动终端用户行为分析已成为一个重要的研究方向。用户点击移动应用的频率在一定程度上反映了他们的偏好。在这项研究中，我们提出了一种基于异构信息网络表示的移动应用点击频率预测模型。该模型首先在用户的移动设备和移动应用之间构建了一个异构的信息网络。为了生成有意义的网络嵌入节点序列，我们在指定的元路径上执行随机游走。最后，通过表征融合和矩阵分解来完成对用户移动应用点击频率的预测。实验表明，我们的方法在平均绝对误差和均方根误差方面优于其他基线方法。因此，将异构信息网络表示方法应用于预测模型是有效的。本研究对移动终端用户的行为研究具有重要意义。