GreedyAdapter: Flexible Web Content Adaptation for Mobile Devices

Rajibul Anam, Chin Kuan Ho, Tek Yong Lim

Abstract


Mobile web browsing usually becomes time-consuming moreover it requires horizontal and vertical scrolling. In addition to this, users interested in only a section of a web page are often burdened with cumbersome whole web contents that not only do not properly fit their mobile screens but also require a lot of delivery time. This problem can be addressed and resolved with the help of a mobile web content adaptation system. The system will enable users to access the target content faster on a mobile device. Existing web content adaptation systems focus on resizing contents to fit a mobile device and removing unnecessary contents from the adapted web page. To the best of our knowledge there is no web content adaptation system that rearranges the web contents to reduce the time taken for locating information on a web page. This research aims to address the gap by proposing a technique for web content adaptation. GreedyAdapter re-arranges the sequence of the blocks from a large web page while maintaining the relationship between the blocks with respect to content. It filters out unnecessary information by allowing users to see the most relevant blocks of a web page. In order to achieve this greedy algorithm is proposed. The proposed algorithm will first assign weights and profits to blocks of a web page. The algorithm will then select the best blocks based on a greedy heuristic and deliver them to handheld devices.

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