Context-Aware Recommendation Model based on Mobile Application Analysis Platform

Recently, various types of log data have been collected and used due to the explosive increase of mobile devices. In mobile environment with high portability and mobility, in addition, the user context information is an important factor for recommendation process. This study attempted to analyze usability log data collected from the mobile device through an application analysis platform. We suggested a context-aware recommendation model to recommend mobile applications or contents by recognizing users’ context data. The usability data of applications consist of activities which were active during the use of a mobile device. The features of these activities are related with time, location and device information. A model proposed in this study has a flexible structure which can be selectively used depending on user circumstances and performs a usability patterns of the applications based on the collaborative filtering method.