Mining the user profile from a smartphone: a multimodal agent framework

—Nowadays smartphones play a significant role in gathering relevant data about their owners. Micro-devices embedded in Personal Digital Assistants (PDAs) perform a continuous sensing, the phone call lists, PIM (Personal Information Manager), text messages and so on allow to collect and mine data enough for a high-level description of daily activities of a user. This paper proposes an agent able to perform an automated profile annotation by adopting Semantic Web languages. As a proof of concept, the devised agent has been tested in an Ambient Intelligence (AmI) scenario, i.e., a domotic environment where it interacts with its home counterpart to trigger services best matching the user needs. A toy example is presented as case study aiming to better clarify the proposal while an early experimental evaluation is reported to assess its effectiveness.