SAVVY: A Semantic Associative Browsing System for Heterogeneous Knowledge Resources

This paper presents a semantic associative browsing system called Semantic Association Various Viewpoint sYstem (SAVVY). Recently, the number of users who employ search engines for not only retrieving Web pages but also understanding or learning an arbitrary concept has been increasing. It is difficult to understand and learn an arbitrary concept by using most of the current search engines, because they provide a list of results according to the input keywords. The proposed approach represents the various relationships between arbitrary concepts as an outline. For example, it is assumed that a user wants information related to an input keyword. Current search engines represent a list of contents that match the keyword. The proposed approach dynamically represents various related concepts and contents on heterogeneous fields by using multiple views that are mutually synchronized. It helps to obtain various contents related to heterogeneous resources while understanding or learning an arbitrary concept.