Scalable Web News Adaptation To Mobile Devices Using Visual Block Segmentation for Ubiquitous Media Services

Abstract

This paper describes an enhanced method of Web content adaptation to mobile devices for online News article provision in ubiquitous environments. Our system exploits a scheme of visual block segmentation for Web pages that filters out unnecessary blocks and extracts useful article information from content blocks. This method resolves the problems of previous approaches to Web content adaptation in which the content transformation to suit to a smaller device is device-dependent and manually-driven. Our method also employs a learning module that is initiated when the user selects to view the full content in the content summary page. As a result of learning, personalization is realized by showing the information for the relevant block at the top of the content list. A series of experiments are performed to evaluate our mobile content adaptation method for a number of well-known Web News sites, and the result of evaluation is satisfactory both in block filtering accuracy and in user satisfaction by personalization.