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VISSYM
2007

Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data

9 years 24 days ago
Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data
Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data sets which are difficult to visualize effectively with standard techniques given the limitations of current display devices. We propose a framework for intelligent time- and data-dependent visual aggregation of data along multiple resolution levels. This idea leads to effective visualization support for long time-series data providing both focus and context. The basic idea of the technique is that either data-dependent or application-dependent, display space is allocated in proportion to the degree of interest of data subintervals, thereby (a) guiding the user in perceiving important information, and (b) freeing required display space to visualize all the data. The automatic part of the framework can accommodate any time series analysis algorithm yielding a numeric degree of interest scale. We apply our techn...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia
Added 30 Sep 2010
Updated 30 Sep 2010
Type Conference
Year 2007
Where VISSYM
Authors Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobias Schreck
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