Abstract
Recently, it has become very hard for users to find their desired mobile services because the number of applications and Web services are rapidly increasing. Therefore, it is important to realize context-aware application recommendation. Because it is necessary to collect large learning data to estimate user's context, we propose a platform for collecting users' context and relationship between context and application by providing an application search system that inquires user's current context. We implemented a system named App.Locky based on our proposal and conducted experiments by publishing the system on the internet. As a result, we confirmed that collected search logs can be used to estimate user's context and relationship between context and application.
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