Resource recommendation for intelligent environments based on a multi-aspect metric

Abstract

Intelligent environments offer information filled spaces. When trying to navigate among all the offered resources users can be overwhelmed. This problem is increased by the heterogeneous nature of resources in smart environments. Users must choose between a plethora of services, multimedia information, interaction modalities and devices. But at the same time the unique characteristics of smart spaces offers us more opportunities to filter these resources. To help users find the resource that they want and need we have designed a multi-aspect recommendation system that takes into account not only the features of the resource and the user, but also context data like the location and current activity. The developed system is flexible enough to be applied to different resource types and scenarios. In this paper we will describe the identified aspects and how they are merged into a single metric. © 2012 Springer-Verlag.