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Mining usage data for adaptive personalisation of smartphone based help-on-demand services

Burns, William, Chen, Liming, Nugent, Chris, Donnelly, Mark, Skillen, Kerry-Louise and Solheim, Ivar (2013) Mining usage data for adaptive personalisation of smartphone based help-on-demand services. In: 6th International Conference on PErvasive Technologies Related to Assistive Environments, Greece. ACM. 8 pp. [Conference contribution]

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URL: http://dx.doi.org/10.1145/2504335.2504377

DOI: doi:10.1145/2504335.2504377


Mobile computing devices and their applications that encompass context aware components are becoming increasingly more prevalent. The context-awareness of these types of applications typically focuses on the services offered. In this paper we describe a framework that supports the monitoring and analysis of mobile application usage patterns with the goal of updating user models for adaptive services and user interface personalisation. This paper focuses on two aspects of the framework. The first is the modelling and storage of the usage data. The second focuses on the data mining component of the framework, outlining the five different capabilities of the adaptation in addition to the algorithms used. The proposed framework has been evaluated through specific case studies, with the results attained demonstrating the effectiveness of the data mining capabilities and in particular the adaptation of the User Interface. The accuracy and efficiency of the algorithms used are also evaluated with three users. The results of the evaluation show that the aims of the data mining component were achieved with the personalisation and adaptation of content and user interface, respectively.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:28963
Deposited By: Dr Mark Donnelly
Deposited On:28 Mar 2014 15:18
Last Modified:28 Mar 2014 15:18

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