Welcome to the InfoSci Platform
Personalisation in Highly Dynamic Grid Services Environments

Personalisation in Highly Dynamic Grid Services Environments

Edgar Jembere, Matthew O. Adigun, Sibusiso S. Xulu
Copyright: © 2009 |Pages: 30
ISBN13: 9781605662466|ISBN10: 1605662461|ISBN13 Softcover: 9781616925413|EISBN13: 9781605662473
DOI: 10.4018/978-1-60566-246-6.ch013
Cite Chapter Cite Chapter

MLA

Jembere, Edgar, et al. "Personalisation in Highly Dynamic Grid Services Environments." Open Information Management: Applications of Interconnectivity and Collaboration, edited by Samuli Niiranen, et al., IGI Global, 2009, pp. 284-313. https://doi.org/10.4018/978-1-60566-246-6.ch013

APA

Jembere, E., Adigun, M. O., & Xulu, S. S. (2009). Personalisation in Highly Dynamic Grid Services Environments. In S. Niiranen, J. Yli-Hietanen, & A. Lugmayr (Eds.), Open Information Management: Applications of Interconnectivity and Collaboration (pp. 284-313). IGI Global. https://doi.org/10.4018/978-1-60566-246-6.ch013

Chicago

Jembere, Edgar, Matthew O. Adigun, and Sibusiso S. Xulu. "Personalisation in Highly Dynamic Grid Services Environments." In Open Information Management: Applications of Interconnectivity and Collaboration, edited by Samuli Niiranen, Jari Yli-Hietanen, and Artur Lugmayr, 284-313. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-246-6.ch013

Export Reference

Mendeley
Favorite

Abstract

Human Computer Interaction (HCI) challenges in highly dynamic computing environments can be solved by tailoring the access and use of services to user preferences. In this era of emerging standards for open and collaborative computing environments, the major challenge that is being addressed in this chapter is how personalisation information can be managed in order to support cross-service personalisation. The authors’ investigation of state of the art work in personalisation and context-aware computing found that user preferences are assumed to be static across different context descriptions whilst in reality some user preferences are transient and vary with changes in context. Further more, the assumed preference models do not give an intuitive interpretation of a preference and lack user expressiveness. This chapter presents a user preference model for dynamic computing environments, based on an intuitive quantitative preference measure and a strict partial order preference representation, to address these issues. The authors present an approach for mining context-based user preferences and its evaluation in a synthetic m-commerce environment. This chapter also shows how the data needed for mining context-based preferences is gathered and managed in a Grid infrastructure for mobile devices.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.