Pervasive Personalisation Workshop
held in conjunction with Pervasive 2010
Eighth International Conference on Pervasive Computing
17-20 May 2010 - Helsinki, Finland
Personalisation is intrinsic the many of the core goals of pervasive computing. The workshop will address the broad range of issues around pervasive personalisation that is based on an explicit user model. One set of key areas concerns the ways that pervasive computing can inform the content of such a model which may be used in the long term for a range of personalised applications. Another set of important topics concern the ways that the model is used for personalisation within a particular application. Common to both of these are the issues of privacy and security of the user model.

Topics for the workshop include, but are not limited to:

  • the nature of user modelling and context modelling, similarities and differences
  • acquisition of user models in pervasive computing
  • machine learning and data mining for pervasive personalisation
  • representation and reasoning about user models that address the particular demands of pervasive personalisation
  • stereotypes in pervasive personalisation
  • long term, lifelong personalisation
  • addressing personalisation for users with special needs
  • addressing privacy, trust and security concerns
  • challenges of personalisation on pervasive interfaces, carried and embedded in the environment
While the key goals of pervasive computing include a strong focus on personalisation, there has been relatively little linkage between research in user modelling and that in pervasive computing. This workshop aims to build stronger links between the range of research communities which provide potential foundations for personalisation in pervasive computing,
Submissions
All submissions will be reviewed by members of the workshop committee. Authors of accepted submissions will be asked to present their work to the workshop. Proceedings will be available in print and on-line.
Classes of submission:
• New research: This is work that has not been previously published. It should present new ideas and work to contribute to the workshop. These contributions will be reviewed and will be included in full in the workshop proceedings. Key criteria for acceptance will be the importance and novelty of the ideas for addressing the challenges of pervasive personalisation.
• Previous work: This is previously published work that is relevant to the workshop. It should be accompanied by an abstract which overviews the work and its relevance to this workshop. Only the abstract will appear in the proceedings.
Submission instructions
Full papers should be up to 8 pages. The submissions must use Springer LNCS style. Papers should be submitted via email to the programme chairs llum@it.usyd.edu.au
Committee
A.J. Brush, Microsoft Research, USA
Keith Cheverst, Lancaster, UK
Peter Dolog, Aalborg University, Denmark
Dominikus Heckmann, DFKI, Saarland University, Germany
Judy Kay, Sydney University, Australia
Tsvi Kuflik, Haifa University, Israel
Bob Kummerfeld, Sydney University, Australia
Antonio Kruger, DFKI, Saarland University, Germany
Marc Langheinrich, University of Lugano, Switzerland
Gord McCalla, University of Saskatchewan, Canada
Petteri Nurmi, Unoversity of Helsinki, Finland
Kurt Partridge, Palo Alto Research Center, USA
James Scott, Microsoft Research, Cambridge, UK
Last change: Sun Jan 31 19:21:37 2010
Important Dates:
@ Submissions: March 12th, 2010
@ Notifications: March 26th, 2010
@ Camera-ready copy: April 15th, 2010
Objectives:
The workshop will focus on the following key questions:
• The nature of user models for pervasive personalisation: what information about a user can and should be captured as a basis for the personalisation? For example, potential sources of user modelling information include: lifelogging; automatically collected sensor data; and personal data across personal machines, devices and in the cloud.
• Representations of personal information about users: what representations meet the particular demands of pervasive personalisation?
• Reasoning about personal information about users: what reasoning mechanisms meet the particular demands of pervasive personalisation?
• Interoperability: how can we ensure that multiple applications can make effective reuse of user models in pervasive personalisation?
• Group modelling: since pervasive personalisation often operates in contexts where the individual user is part of a group, how can the personalisation address the needs of the group and how can the personalisation delivered to an individual take account of the others present?
• Privacy: how can the particular privacy demands of pervasive personalisation be addressed effectively?
• User control: how can we ensure users can control their user model and the personalisation in pervasive environments?
• Domains: are there domain specific solutions to pervasive personalisation, where the particular demands of the domain affect the user modelling and personalisation approaches?
• Grand Challenge Problems: how can we address the personalisation challenges that are at the heart of Grand Challenge Problems identified by peak research bodies, notably, personalised learning, identified by Computing Research Association, UKCRC National Academy of Engineering and lifelong memories UKCRC.