Interactive visualization for opportunistic exploration of large document collections

an article by Simon Lehmann, Ulrich Schwanecke and Ralf Dörner (RheinMain University of Applied Sciences, Wiesbaden) published in Information Systems Volume 35 Issue 2 (April 2009)

Abstract
Finding relevant information in a large and comprehensive collection of cross-referenced documents like Wikipedia usually requires a quite accurate idea where to look for the pieces of data being sought. A user might not yet have enough domain-specific knowledge to form a precise search query to get the desired result on the first try. Another problem arises from the usually highly cross-referenced structure of such document collections. When researching a subject, users usually follow some references to get additional information not covered by a single document. With each document, more opportunities to navigate are added and the structure and relations of the visited documents gets harder to understand.
This paper describes the interactive visualisation Wivi which enables users to intuitively navigate Wikipedia by visualising the structure of visited articles and emphasising relevant other topics. Combining this visualisation with a view of the current article results in a custom browser specially adapted for exploring large information networks. By visualising the potential paths that could be taken, users are invited to read up on subjects relevant to the current point of focus and thus opportunistically finding relevant information. Results from a user study indicate that this visual navigation can be easily used and understood. A majority of the participants of the study stated that this method of exploration supports them finding information in Wikipedia.

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