Content selection model for adaptive content delivery

Authors:
Chen Ding;Shutao Zhang;Chi-Hung Chi
Affiliations:
School of Computer Science, Ryerson University, Canada;School of Computing, National University of Singapore, Singapore;School of Software, Tsinghua University, Beijing, China
Venue:
APPT'05 Proceedings of the 6th international conference on Advanced Parallel Processing Technologies
Year:
2005

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Abstract

In order to adapt content delivery to different client capabilities and preferences, we propose a content selection model to automatically classify HTML content based on its functionality, then map client descriptions on preferences and device capabilities into our classification scheme, and finally selectively deliver the content which users want and which devices can handle. The experiment shows that our content selection model could reduce HTML object size, object latency and page latency. Therefore, it is effective in saving network resources and improving clients’ access experiences.