@INPROCEEDINGS{NurmiCAMS2006,
  author = {Petteri Nurmi and Alfons Salden and Sian Lun Lau and Jukka Suomela
	and Michael Sutterer and Jean Millerat and Miquel Martin and Eemil
	Lagerspetz and Remco Poortinga},
  title = {A system for context-dependent user modelling},
  booktitle = {On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops},
  year = {2006},
  volume = {Volume 4278/2006},
  series = {Lecture Notes in Computer Science},
  pages = {1894-1903},
  address = {Montpellier, France},
  month = {October},
  publisher = {Springer-Verlag},
  note = {Presented at the Second International Workshop on Context-Aware Mobile
	Systems (CAMS'06)},
  abstract = {We present a system for learning and utilizing context-dependent user
	models. The user models attempt to capture the interests of a user
	and link the interests to the situation of the user. The models are
	used for making recommendations to applications and services on what
	might interest the user in her current situation. In the design process
	we have analyzed several mock-ups of new mobile, context-aware services
	and applications. The mock-ups spanned rather diverse domains, which
	helped us to ensure that the system is applicable to a wide range
	of tasks, such as modality recommendations (e.g., switching to speech
	output when driving a car), service category recommendations (e.g.,
	journey planners at a bus stop), and recommendations of group members
	(e.g., people with whom to share a car). The structure of the presented
	system is highly modular. First of all, this ensures that the algorithms
	that are used to build the user models can be easily replaced. Secondly,
	the modularity makes it easier to evaluate how well different algorithms
	perform in different domains. The current implementation of the system
	supports rule based reasoning and tree augmented naive Bayesian classifiers
	(TAN). The system consists of three components, each of which has
	been implemented as a web service. The entire system has been deployed
	and is in use in the EU IST project MobiLife. In this paper, we detail
	the components that are part of the system and introduce the interactions
	between the components. In addition, we briefly discuss the quality
	of the recommendations that our system produces.},
  doi = {10.1007/11915072_97},
  owner = {Miquel Martin},
  pdf = {http://www.springerlink.com/content/f4304745t8470300/fulltext.pdf}
}