Adapting web pages using graph partitioning algorithms for user-centric multi-device web browsing

In the era of ubiquitous computing, applications are emerging to benefit from using devices of different users and different capabilities together. This paper focuses on user-centric web browsing using multiple devices, where content of a web page is partitioned, adapted and allocated to devices in the vicinity. We contribute two novel web page partitioning algorithms. They differ from existing approaches by allowing for both, automatic and semi-automatic partitioning. On the one hand, this provides good automatic, web page independent results by utilizing sophisticated structural pre- and postprocessing of the web page. On the other hand, these results can be improved by considering additional semantic information provided through user-generated web page annotations. We further present a performance evaluation of our algorithms. Moreover, we contribute the results of a user study. These clearly show that (1) our algorithms provide good automatic results and (2) the application of user-centric, annotation-based semantic information leads to a significantly higher user satisfaction.