A Hybrid Preference Learning and Context Refinement Architecture

Abstract

Pervasive computing envisions a world where people are surrounded by numerous communication and computing interconnected devices that are invisible and assist users in their everyday tasks in a seamless unobtrusive manner. Most pervasive computing research initiatives aim towards the realization of smart spaces, i.e. fixed spaces that provide pervasive features in a static and geographically limited environment. To bridge these isolated pervasive spaces, the EU project Persist has introduced the concept of self-improving Personal Smart Spaces (PSSs) that follow their owners wherever they go. This paper provides an overview of the context and preference learning facilities that have been designed to support the realization of PSSs and enhance their proactivity and self-improvement features.