Learning Behaviour for Service Personalisation and Adaptation

Luke Chen, Kerry-Louise Skillen, William Burns, Susan Quinn, Joseph Rafferty, CD Nugent, MP Donnelly, Ivar Solheim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)
127 Downloads (Pure)


Context-aware applications within pervasive environments are increasingly being developed as services and deployed in the cloud. As such these services are increasingly required to be adaptive to individual users to meet their specific needs or to reflect the changes of their behavior. To address this emerging challenge this paper introduces a service-oriented personalisation framework for service personalisation with special emphasis being placed on behavior learning for user model and service function adaptation. The paper describes the system architecture and the underlying methods and technologies including modelling and reasoning, behavior analysis and a personalisation mechanism. The approach has been implemented in a service-oriented prototype system, and evaluated in a typical scenario of providing personalised travel assistance for the elderly using the help-on-demand services deployed on smartphone.
Original languageEnglish
Title of host publicationLearning Behaviour for Service Personalisation and Adaptation. Machine Learning and Cybernetics
Number of pages6
ISBN (Electronic)978-3-662-45652-1
ISBN (Print) 978-3-662-45651-4
Publication statusPublished (in print/issue) - 5 Dec 2014


  • Personalisation
  • Behavior learning
  • Adaptation
  • Pervasive systems
  • Semantic modeling
  • Assistive Living


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