Local App Classification using Deep Neural Network based on Mobile App Market Data

摘要

Due to the spread of smartphones, mobile applications (app) have been widely used in daily life. Several apps which provide real-world related information (called "local apps") are useful for not only tourist but also residents. There is a category that seems to contain local apps in app market such as "Travel & Local" in Google Play, but many local apps are categorized into other categories. Thus, we present a method to classify local apps based on app market data using deep neural network (DNN). We leverage the fact that each app is manually labeled by developer to pre-train the DNN. In addition, we create features from an app market data because app markets involve multi-modal data such as app name, category and number of installs. We conducted an experiment on a real-world dataset crawled from Google Play to validate the effectiveness of the proposed method. Our evaluation shows that the proposed method outperforms the baseline method by 5.5% regarding F1 score.