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1.
FINDING PATTERNS
IN TEMPORAL DATA
osium!
CI L Symp
KRIST WONGSUPHASAWAT 27th H 010!
, 2
May 27
TAOWEI DAVID WANG
CATHERINE PLAISANT
BEN SHNEIDERMAN
HUMAN-COMPUTER INTERACTION LAB
UNIVERSITY OF MARYLAND
2.
FINDING PATTERNS
IN TEMPORAL DATA
osium!
CI L Symp
KRIST WONGSUPHASAWAT 27th H 010!
, 2
May 27
TAOWEI DAVID WANG
CATHERINE PLAISANT
BEN SHNEIDERMAN
HUMAN-COMPUTER INTERACTION LAB
UNIVERSITY OF MARYLAND
3.
TEMPORAL CATEGORICAL DATA
• A type of time series
Event! Category! Event!
Numerical!
Stock: Microsoft Patient ID: 45851737
$'#")#"$!$&!$($$ &0!B$0& !"#$"#"$$%&!'(") &*++,-./&
$'#")#"$!$&!$(!; &0!B$!& !"#$"#"$$%&!'(0) &123+43567&
$'#")#"$!$&!$(0$ &0!B$"& !"#$"#"$$%&""('' &89:&
$'#")#"$!$&!$('; &0!B$%& !"#$;#"$$%&$;($< &=/>>+&
$'#")#"$!$&!!($$ &0!B!)& !"#!'#"$$%&$)(!? &1@,A&
& Time
Arrival
Emergency
ICU
Floor
Exit
4.
TEMPORAL CATEGORICAL DATA
Electronic Health Records: symptoms, treatment, lab test"
Traffic incident logs: arrival/departure time of each unit"
Student records: course, paper, proposal, defense, etc."
"
Others: web logs, usability study logs, etc."
5.
10+ years work on temporal visualization
(mostly on Electronic Health Records)
6.
LIFELINES
D
SINGLE RECOR
[Plaisant et al. 1998]
http://www.cs.umd.edu/hcil/lifelines
8.
working with physicians at
WASHINGTON HOSPITAL CENTER
9.
EXAMPLE DATA
• Patient transfers
ARRIVAL Arrive the hospital
EMERGENCY Emergency room
ICU Intensive Care Unit
INTERMEDIATE Intermediate Medical Care
FLOOR Normal room
EXIT-ALIVE Leave the hospital alive
EXIT-DEAD Leave the hospital dead
10.
TASKS
• Example: Finding “Bounce backs”
ICU Floor ICU
within 2 days
11.
LIFELINES 2
RECORD
D
R ECOR
RECORD
RECORD
RECORD
[Wang et al. 2008, 2009]
http://www.cs.umd.edu/hcil/lifelines2
12.
Multiple Records ARF (Align-Rank-Filter)
Framework
Temporal Summary
LifeLines2 – Search and Visualize
13.
ALIGNMENT
• Sentinel events as reference points
Time
June July August
Patient #45851737 Arrival
Emergency
ICU
Floor
Exit
Patient #43244997 Arrival
Emergency
ICU
Floor
Exit
18.
FINDING “BOUNCE BACKS”
Before After
• Much faster to specify new query
• Visualizing the results gives better understanding
19.
USER STUDIES: SEARCH
LifeLines2 Similan
Exact! Similarity-based!
MUST have A, B, C SHOULD have A, B, C
Query Query
Record#2 Record#2
more
Record#1 Record#1
similar
Record#3 Record#3
20.
USER STUDIES: SEARCH
LifeLines2 Similan
Exact! Similarity-based!
MUST have A, B, C SHOULD have A, B, C
Query Query
1 Record#2 Record#2
more
Record#1 Record#1
similar
Record#3 Record#3