Relaxed selection techniques for querying time-series graphs

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Relaxed selection techniques for querying time-series graphs
Time-series graphs are often used to visualize phenomena that change over time. Common tasks include comparing values at different points in time and searching for specified patterns, either exact or approximate. However, tools that support time-series graphs typically separate query specification from the actual search process, allowing users to adapt the level of similarity only after specifying the pattern. We introduce relaxed selection techniques, in which users implicitly define a level of similarity that can vary across the search pattern, while creating a search query with a single-gesture interaction. Users sketch over part of the graph, establishing the level of similarity through either spatial deviations from the graph, or the speed at which they sketch (temporal deviations). In a user study, participants were significantly faster when using our temporally relaxed selection technique than when using traditional techniques. In addition, they achieved significantly higher pr...
Christian Holz, Steven Feiner
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where UIST
Authors Christian Holz, Steven Feiner
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