Context-aware interactive content adaptation
Proceedings of the 4th international conference on Mobile systems, applications and services
A Flexible Content Adaptation System Using a Rule-Based Approach
IEEE Transactions on Knowledge and Data Engineering
URICA: Usage-awaRe Interactive Content Adaptation for mobile devices
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
Mobility '07 Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology
Correlation-based content adaptation for mobile web browsing
Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware
Preference-based adaptation of multimedia presentations for different display sizes
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
CDVE'07 Proceedings of the 4th international conference on Cooperative design, visualization, and engineering
Correlation-based content adaptation for mobile web browsing
MIDDLEWARE2007 Proceedings of the 8th ACM/IFIP/USENIX international conference on Middleware
User Modeling and User-Adapted Interaction
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Mobile devices are increasingly being used to access Web content but lack the resources for proper presentation to the user. To address this problem, content is typically adapted to be more suitable for a mobile environment. Community-Driven Adaptation (CDA) is a novel approach to automatic content adaptation for mobile devices that adapts content based on feedback from users. CDA groups users into communities based on common characteristics, and assumes that users of the same community have similar adaptation requirements. CDA learns how to adapt content by observing how members of a community alter adapted content to make it more useful to them. Experiments that consider the idealized case, where all users perform the same task, show that CDA can reduce wastage of network bandwidth by up to 90% and requires less user interaction to correct bad adaptation decisions compared with existing approaches to automatic content adaptation.