TY - JOUR
T1 - Querying event sequences by exact match or similarity search
T2 - Design and empirical evaluation
AU - Wongsuphasawat, Krist
AU - Plaisant, Catherine
AU - Taieb-Maimon, Meirav
AU - Shneiderman, Ben
N1 - Funding Information:
We appreciate support from the National Institutes of Health (NIH) Grant CA147489 and Washington Hospital Center , and collaboration from our physician partners at the Washington Hospital Center, especially Dr. Phuong Ho, Dr. Mark Smith and David Roseman, and would like to thank Dr. Vibha Sazawal, Dr. Jen Golbeck, Dr. Taowei David Wang and Sureyya Tarkan for their thoughtful comments, and all participants in the studies for their participations.
PY - 2012/1/1
Y1 - 2012/1/1
N2 - Specifying event sequence queries is challenging even for skilled computer professionals familiar with SQL. Most graphical user interfaces for database search use an exact match approach, which is often effective, but near misses may also be of interest. We describe a new similarity search interface, in which users specify a query by simply placing events on a blank timeline and retrieve a similarity-ranked list of results. Behind this user interface is a new similarity measure for event sequences which the users can customize by four decision criteria, enabling them to adjust the impact of missing, extra, or swapped events or the impact of time shifts. We describe a use case with Electronic Health Records based on our ongoing collaboration with hospital physicians. A controlled experiment with 18 participants compared exact match and similarity search interfaces. We report on the advantages and disadvantages of each interface and suggest a hybrid interface combining the best of both.
AB - Specifying event sequence queries is challenging even for skilled computer professionals familiar with SQL. Most graphical user interfaces for database search use an exact match approach, which is often effective, but near misses may also be of interest. We describe a new similarity search interface, in which users specify a query by simply placing events on a blank timeline and retrieve a similarity-ranked list of results. Behind this user interface is a new similarity measure for event sequences which the users can customize by four decision criteria, enabling them to adjust the impact of missing, extra, or swapped events or the impact of time shifts. We describe a use case with Electronic Health Records based on our ongoing collaboration with hospital physicians. A controlled experiment with 18 participants compared exact match and similarity search interfaces. We report on the advantages and disadvantages of each interface and suggest a hybrid interface combining the best of both.
KW - Event sequence
KW - Similan
KW - Similarity measure
KW - Similarity search
KW - Temporal categorical data
KW - Temporal query interface
UR - http://www.scopus.com/inward/record.url?scp=84857286889&partnerID=8YFLogxK
U2 - 10.1016/j.intcom.2012.01.003
DO - 10.1016/j.intcom.2012.01.003
M3 - Article
AN - SCOPUS:84857286889
SN - 0953-5438
VL - 24
SP - 55
EP - 68
JO - Interacting with Computers
JF - Interacting with Computers
IS - 2
ER -