Interactive Pattern Search in Time Series
(Using TimeSearcher 2)
Paolo Buono, Aleks Aris, Catherine Plaisant,
Amir Khella, and Ben Shneiderman
Proceedings, Conference on Visual Display and Analysis, 2005
Presented to CMSC 838S (Information Visualization)
By Derek Juba & Scott Nestler
On Feb. 16, 2006
Outline
• Introduction
• Related Work
• TimeSearcher 2 Demo
• Key Contributions
• Future Work
• Conclusions
Introduction
• Time series- sequence of real numbers,
representing observations of variable at equal
time intervals
• Many applications of time series (e.g. EKGs,
seismographs, digital recordings)
• Traditional analyses are based in classical
statistics
• Now able to explore time series data with
visualization tools
• TimeSearcher 2 designed for range of
users; statistical analysis skills not required
Introduction (cont)
• Timebox- rectangular region that is
selected and directly manipulated on a
timeline overview of data
– Boundaries of timeboxes used to specify
parameters for query
– Two types
• Original- used to filter data and reduce scope
of search
• New- used to perform specific pattern search in
remaining data
Related Work
• Diamond Fast (Unwin & Wills, 1999)
– Allows visualization, moving, resizing
– Only manages short time series
• ILOG & Personal Stock Monitor
– High level of interaction with enhanced
zoom
– Lack search capabilities; limited to a single
time series
• Semantic zoom (Brodbeck, Girardin,
2003)
• Spiral view(Carlis & Konstan, 1998)
Related Work (cont)
• Time Searcher 1- patterns specified
with timeboxes
• Choratas- pattern specified numerically
• VizTree- pattern specified in segments
• QuerySketch- allows direct sketching
of pattern
• IPBC- 3D tool allows selecting pattern
in data; for periodic data
No known tool other than TimeSearcher allows
specifying multiple patterns on multiple variables
TimeSearcher 2 Demo
Demo
Key Contributions
•
Three-step interactive search
1. Reduce scope with timebox(es)
2. Specify a pattern to search for
3. Refine query dynamically
•
Search algorithm
– Uses modified Euclidean distance
between two time series
– Transformations available
•
•
•
•
Offset translation
Magnitude scaling
Linear trend removal
Noise reduction
Future Work
• Dealing with larger datasets
• Improved interaction
– Search pattern selection
• Dealing with missing data
– Ignore?
– Estimate?
• Evaluation
Conclusions
• Room for improvement in interactive
exploration of time series
– Improved algorithms
– Interactive interfaces
• Interactive search used with
traditional features aids exploratory
analysis
• Three-step framework applicable to
larger data archives