Proceedings Second International Workshop on User Interfaces in Data Intensive Systems. UIDIS 2001
DOI: 10.1109/uidis.2001.929925
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Search result visualisation with xFIND

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Cited by 22 publications
(13 citation statements)
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“…Displaying results as points looks similar to star maps and thus, in some systems the idea of a map has been explicitly used and the clusters are represented as countries or islands. Figure 6 shows a cluster-based result view where clusters are presented as islands (K. Andrews, Gutl, Moser, Sabol, & Lackner, 2001).…”
Section: -Dimensional Results Viewsmentioning
confidence: 99%
“…Displaying results as points looks similar to star maps and thus, in some systems the idea of a map has been explicitly used and the clusters are represented as countries or islands. Figure 6 shows a cluster-based result view where clusters are presented as islands (K. Andrews, Gutl, Moser, Sabol, & Lackner, 2001).…”
Section: -Dimensional Results Viewsmentioning
confidence: 99%
“…These map-style visualisations are based on a spatial metaphor whereby similar documents (or themes) are clustered together and placed physically nearer to each other. They have been used for a range of applications, including providing thematic clustering of search results [1] and document collections [8], helping software developers make sense of large repositories of source code [17], allowing users to explore music libraries where "islands" on the map represent different genres or styles of music [26], and visualising user traffic on the Internet radio station last.fm [22].…”
Section: Spatial Metaphors For Information Visualisationmentioning
confidence: 99%
“…Early attempts include systems such as xFind [3], Envision [90], and FilmFinder [1]. As t hese interfaces may overwhelm some searchers, Shneiderman et al proposed a simplified display called Hieraxes [100] (see Figure 2.5) .…”
Section: Document Spatializationmentioning
confidence: 99%
“…In xFind [3], the Visisland interface was developed in addition to t he scatterplot and a list-based representation to display thematic clustering of search results. First, cluster centroids are randomly mapped to t he display, and then documents are located in a ring around the corresponding cluster while documents that are more similar are placed closer to each other.…”
Section: Document Cluster Visualizationmentioning
confidence: 99%
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