Combining empirical experimentation and modeling techniques : A design research approach for personalized mobile advertising applications
Related Research Unit(s)
|Journal / Publication||Decision Support Systems|
|Online published||13 Oct 2007|
|Publication status||Published - Feb 2008|
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-37049030218&origin=recordpage|
We propose a design research approach combining behaviour and engineering techniques to better support user modeling in personalized mobile advertising applications. User modeling is a practical means of enabling personalization; one important method to construct user models is that of Bayesian networks. To identify the Bayesian network structure variables and the prior probabilities, empirical experimentation is adopted and context, content, and user preferences are the salient variables. User data collected from the survey are used to set the prior probabilities for the Bayesian network. Experimental evaluation of the system shows it is effective in improving user attitude toward mobile advertising.
- Bayesian networks, Mobile advertising, Mobile commerce, Personalization, User modeling
Decision Support Systems, Vol. 44, No. 3, 02.2008, p. 710-724.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review