Journal article
Discovering frequent user--environment interactions in intelligent environments
Personal and ubiquitous computing, Vol.16(1), pp.91-103
01/2012
Handle:
https://hdl.handle.net/2376/118199
Abstract
Intelligent Environments are expected to act proactively, anticipating the user’s needs and preferences. To do that, the environment must somehow obtain knowledge of those need and preferences, but unlike current computing systems, in Intelligent Environments, the user ideally should be released from the burden of providing information or programming any device as much as possible. Therefore, automated learning of a user’s most common behaviors becomes an important step towards allowing an environment to provide highly personalized services. In this article, we present a system that takes information collected by sensors as a starting point and then discovers frequent relationships between actions carried out by the user. The algorithm developed to discover such patterns is supported by a language to represent those patterns and a system of interaction that provides the user the option to fine tune their preferences in a natural way, just by speaking to the system.
Metrics
19 Record Views
Details
- Title
- Discovering frequent user--environment interactions in intelligent environments
- Creators
- Asier Aztiria - University of Mondragon Mondragon SpainJuan Augusto - University of Ulster Jordanstown UKRosa Basagoiti - University of Mondragon Mondragon SpainAlberto Izaguirre - University of Mondragon Mondragon SpainDiane Cook - Washington State University Pullman WA USA
- Contributors
- Enrico Rukzio (Editor)Johannes Schöning (Editor)Michael Rohs (Editor)Jonna Häkkilä (Editor)Raimund Dachselt (Editor)Jonna Häkkilä (Editor)Raimund Dachselt (Editor)Johannes Schöning (Editor)Michael Rohs (Editor)
- Publication Details
- Personal and ubiquitous computing, Vol.16(1), pp.91-103
- Academic Unit
- School of Electrical Engineering and Computer Science
- Publisher
- Springer-Verlag; London
- Identifiers
- 99900548319601842
- Language
- English
- Resource Type
- Journal article