Relaxed Selection Techniques for
Querying Time-Series Graphs

mit Steven Feiner

Abbildung 1

Relaxed Selection Techinques: Figure 1

(für ein hochauflösendes Bild klicken)

Relaxed selection techniques. Spatially relaxed selection (top): Tolerances are derived from spatial deviations between displayed graph and user sketch on a point-by-point basis. Temporally relaxed selection (bottom): Tolerances are derived from input speed. (Center) In both cases, tolerances can be visualized with circles around points in the selection. (Right) Tolerant selections allow similarity matches for patterns that recur in a time series.

Zusammenfassung

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 precision and recall with our spatially relaxed selection technique compared to traditional techniques.

Video

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As shown in the video, the application SoftSelect implements two sketch-based tools and approaches to select parts from a graph. Both techniques allow the user to specify fuzzy queries by selecting a part of the graph and relaxing similarity constraints for the query. A subsequent matching process evaluates these relaxed selections and searches for matching patterns in a graph, i.e., it matches the query against all parts of the graph, highlighting those parts that exhibit the pattern within the defined constraints. In a nutshell, a part of a graph is a match if it follows the general pattern of the specified query and passes through the areas of tolerances (relaxed matches, tolerances are visualized with circles).

Veröffentlichung

BibTeX

@inproceedings{holz2009,
    author = {Holz, Christian and Feiner, Steven},
    title = {Relaxed selection techniques for querying time-series graphs},
    booktitle = {UIST '09: Proceedings of the 22nd annual ACM symposium on User interface software and technology},
    year = {2009},
    isbn = {978-1-60558-745-5},
    pages = {213--222},
    location = {Victoria, BC, Canada},
    doi = {http://doi.acm.org/10.1145/1622176.1622217},
    publisher = {ACM},
    address = {New York, NY, USA},
}