Querying event sequences by exact match or similarity search: Design and empirical evaluation

  • Authors:

  • Krist Wongsuphasawat;Catherine Plaisant;Meirav Taieb-Maimon;Ben Shneiderman

  • Affiliations:

  • Human-Computer Interaction Lab, University of Maryland, College Park, MD, USA and Department of Computer Science, University of Maryland, College Park, MD, USA;Human-Computer Interaction Lab, University of Maryland, College Park, MD, USA;Human-Computer Interaction Lab, University of Maryland, College Park, MD, USA and Ben-Gurion University of the Negev, Beer-Sheva, Israel;Human-Computer Interaction Lab, University of Maryland, College Park, MD, USA and Department of Computer Science, University of Maryland, College Park, MD, USA

  • Venue:
  • Interacting with Computers
  • Year:
  • 2012

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Abstract

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.