document: Browsing fatigue in handhelds : semantic bookmarking spells relief Focused Web browsing activities such as periodically looking up headline news , weather reports , etc. , which require only selective fragments of particular Web pages , can be made more efficient for users of limited-display-size handheld mobile devices by delivering only the target fragments . Semantic bookmarks provide a robust conceptual framework for recording and retrieving such targeted content not only from the specific pages used in creating the bookmarks but also from any user-specified page with similar content semantics . This paper describes a technique for realizing semantic bookmarks by coupling machine learning with Web page segmentation to create a statistical model of the bookmarked content . These models are used to identify and retrieve the bookmarked content from Web pages that share a common content domain . In contrast to ontology-based approaches where semantic bookmarks are limited to available concepts in the ontology , the learning-based approach allows users to bookmark ad-hoc personalized semantic concepts to effectively target content that fits the limited display of handhelds . User evaluation measuring the effectiveness of a prototype implementation of learning-based semantic bookmarking at reducing browsing fatigue in handhelds is provided .
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