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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. Keywords—Ambient Intelligence; Agent-based Data Mining; Semantic Web of Things; Home and Building Automation.