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.
This research is supported by the funding 2004CB719400 of China.
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© 2005 Springer-Verlag Berlin Heidelberg
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Ding, C., Zhang, S., Chi, CH. (2005). Content Selection Model for Adaptive Content Delivery. In: Cao, J., Nejdl, W., Xu, M. (eds) Advanced Parallel Processing Technologies. APPT 2005. Lecture Notes in Computer Science, vol 3756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573937_49
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DOI: https://doi.org/10.1007/11573937_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29639-3
Online ISBN: 978-3-540-32107-1
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