The development and implementation of web content adaptation and negotiation based on user, device and network profiles / Harizah Sazali

The ability to access learning materials anywhere, anytime on any device is a
defining feature of today modern learning environment. However, the differences in
processing power, storage and display resolution of mobile terminals will lead to
some problems that the same content is sent to heterogeneous terminals. Although
content adaptation techniques have been extensively studied for mobile computing
systems in last decades, most of the previous work focused on adaptation with
respect to terminal capabilities. Since the personalized learning pattern has received
tremendous interests in recent years, it is unsuitable to send the same media type of
content to the different learners. With respect to the problems, it is needed to adapt
content to characteristics of terminals and preferences of learners. In this project, we
propose a page and video adaptation algorithms employing a mechanism to extract
the semantic structure of an existing web page and a modular page splitting scheme
to partition the web page into smaller and logically related content blocks or reduce
the size of the distributed content. Based on the experiment results, it is proved that
content adaptation under e-learning environment can be achieved by the algorithms
effectively.