ADaPT: Automatic Data Personalization based on contextual preferences

Abstract

This demo presents a framework for personalizing data access on the basis of the users' context and of the preferences they show while in that context. The system is composed of (i) a server application, which “tailors” a view over the available data on the basis of the user's contextual preferences, previously inferred from log data, and (ii) a client application running on the user's mobile device, which allows to query the data view and collects the activity log for later mining. At each change of context detected by the system the corresponding tailored view is loaded on the client device: accordingly, the most relevant data is available to the user even when the connection is unstable or lacking. The demo features a movie database, where users can browse data in different contexts and appreciate the personalization of the data views according to the inferred contextual preferences.