Supporting Search Result Browsing and Exploration via Cluster-Based Views and Zoom-Based Navigation
Karol Rástočný, Michal Tvarožek, M´ria Bielikov´ · 2011
The difficulty of finding relevant information in the Web is increasing as web repositories grow in size. We propose a novel approach for navigation in the Semantic Web, which helps users find relevant information and enables them to browse similar and/or related resources. We achieve this via view-based search using navigation in a two-dimensional graph, which has the advantage of visualizing dependencies between results. We address problems with readability and understandability via adaptive views, result clustering, facet marking, next action recommendation and zoom-based navigation.