An algorithm for drawing general undirected graphs
Information Processing Letters
Bead: explorations in information visualization
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Map displays for information retrieval
Journal of the American Society for Information Science
Visualization and scaling of TREC topic document sets
Information Processing and Management: an International Journal
Aspect windows, 3-D visualizations, and indirect comparisons of information retrieval systems
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Mapping semantic information in virtual space: dimensions, variance and individual differences
International Journal of Human-Computer Studies - Empirical evaluation of information visualizations
Communications of the ACM
Evaluating combinations of ranked lists and visualizations of inter-document similarity
Information Processing and Management: an International Journal - Special issue on interactivity at the text retrieval conference (TREC)
Using clustering and classification approaches in interactive retrieval
Information Processing and Management: an International Journal - Special issue on interactivity at the text retrieval conference (TREC)
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The effectiveness of query-specific hierarchic clustering in information retrieval
Information Processing and Management: an International Journal
Footprints of information foragers: behaviour semantics of visual exploration
International Journal of Human-Computer Studies
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Interactive information organization: techniques and evaluation
Interactive information organization: techniques and evaluation
Topic modeling for mediated access to very large document collections
Journal of the American Society for Information Science and Technology
Browsing a document collection represented in two-and three-dimensional virtual information space
International Journal of Human-Computer Studies
Binary pathfinder: an improvement to the pathfinder algorithm
Information Processing and Management: an International Journal - Special issue: Informetrics
Local multidimensional scaling
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Information Visualization: Beyond the Horizon
Information Visualization: Beyond the Horizon
International Journal of Human-Computer Studies
Comparison of visualization methods for an atlas of gene expression data sets
Information Visualization
A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time
Information Processing and Management: an International Journal
Visualizing evolving networks: minimum spanning trees versus pathfinder networks
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
A cartographic approach to visualizing conference abstracts
IEEE Computer Graphics and Applications
Navigating tomorrow's web: From searching and browsing to visual exploration
ACM Transactions on the Web (TWEB)
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Previous work has shown that distance-similarity visualisation or 'spatialisation' can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or 'cluster growing' strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of nonmetric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion.