Lifelong User Modelling
Judy Kay, Bob Kummerfeld
School of Information Technologies, University of Sydney
Contact Person
Judy Kay
judy@it.usyd.edu.au
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Project Description
Pervasive and ubiquitous computing offers significant potential for improving our lives.
A feature of pervasive and ubiquitous computing is that it collects and moves
huge amounts of data that are about us or belong to us.
This huge and fast-growing collection of personal data offers great potential benefits, including
augmented cognition and life-long memories:
providing people with ready access to pertinent information about themselves
from their own data stores will enable them to expand their effective
cognition and knowledge beyond what they would otherwise remember.
Life-long learning is another potential benefit, with the possibility
that we can learn precisely when and where we need to, with learning
resources delivered just for us, taking account of our existing knowledge
and preferred ways of learning. While these benefits are significant,
they will be accompanied by the issue of how individuals' privacy will be safeguarded.
There is an essential trade-off between the benefits of capturing and
using personal data and the risk to privacy.
Whatever the outcome of the debate on this trade-off,
people need to be empowered technically to determine their own preferences for
storing, accessing and using their personal information.
This project aims to create the science and technology that will allow
people to control their personal information and its use in pervasive
computing environments.
Key Publications
J. Kay and B. Kummerfeld, editors. Proceeding of the Lifelong User Modelling Workshop at UMAP'09 User Modeling Adaptation, and Personalization, 2009. [View Details]
G. Darke, J. Kay, and B. Kummerfeld. Mobile personalisation: new challenges for privacy. In Ubiquitous User Modeling, at UMAP 2009, pages 37-40, 2009. [View Details]
J. Kay and B. Kummerfeld. Lifelong user modelling goals, issues and challenges. In Proceeding of the Lifelong User Modelling Workshop at UMAP'09 User Modeling Adaptation, and Personalization, pages 27-34, 2009. [View Details]
P. Dolog, J. Kay, and B. Kummerfeld. Personal lifelong user model clouds. In Proceeding of the Lifelong User Modelling Workshop at UMAP'09 User Modeling Adaptation, and Personalization, pages 1-8, 2009. [View Details]
R. Gluga and J. Kay. Largescale, long-term learner models supporting flexible curriculum definition. In Proceedings of the Workshop on Scalability Issues in AIED, held in conjunction with AIED2009, pages 10-19, 2009. [View Details]
J. Bunton, J. Kay, and B. Kummerfeld. Metaview: Dynamic metadata based views of user files. In R. McArthur, P. Thomas, A. Turpin, and M. Wu, editors, Australian Document Computing Symposium, pages 11-19, 2008. [View Details]
J. Kay. Lifelong learner modeling for lifelong personalized pervasive learning. IEEE Trans on Learning Technologies, 1(4):215-228, 2008. [View Details]
S. Bull and J. Kay. Student models that invite the learner in: The SMILI open learner modelling framework. IJAIED, International Journal of Artificial Intelligence, 17(2):89-120, 2007. [View Details]
S. Bull and J. Kay. Student models that invite the learner in: The SMILI open learner modelling framework. Technical Report 580, School of IT, The University of Sydney, January 2006. [View Details]
J. Kay. Scrutable adaptation: because we can and must. In V. Wade, H. Ashman, and B.Smyth, editors, Proceedings of Adaptive Hypermedia and Adaptive Web-Based Systems, 4th International Conference, AH2006, pages 11-19. Springer, 2006. [View Details]
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