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Proceedings Paper

Visual-spatial exploration of thematic spaces: a comparative study of three visualization models
Author(s): Timothy Cribbin; Chaomei Chen
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Paper Abstract

Scatter graphs are a popular medium for visualizing spatial- semantic structures derived from abstract information spaces. For small spaces such graphs can be an effective means of reducing high-dimensional information into two or three spatial dimensions. As dimensionally increases, representing the thematic diversity of documents using spatial proximity alone becomes less and less effective. This paper reports an experiment designed to determine whether, for larger spaces, benefits are to be gained from adding visual links between document nodes as an additional means of representing the most important semantic relationships. Two well known algorithms, minimum spanning trees (MST) and pathfinder associative networks (PFNET), were tested against both a scatter graph visualization, derived from factor analysis, and a traditional list-based hypertext interface. It was hypothesized that visual links would facilitate users' comprehension of the information space with corresponding gains in information space with corresponding gains in information seeking performance. Navigation performance and user impression were analyzed across a range of different search tasks. Results indicate both significant performance gains and more positive user feedback for MST and PFNET visualizations over scatter graphs. Performance on all visualizations was generally poorer and never better than that achieved on the text list interface although the magnitude of these differences was found to be highly task dependent.

Paper Details

Date Published: 3 May 2001
PDF: 11 pages
Proc. SPIE 4302, Visual Data Exploration and Analysis VIII, (3 May 2001); doi: 10.1117/12.424929
Show Author Affiliations
Timothy Cribbin, Brunel Univ. (United Kingdom)
Chaomei Chen, Brunel Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 4302:
Visual Data Exploration and Analysis VIII
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Craig M. Wittenbrink; Matti Grohn, Editor(s)

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