Efficient pattern-based querying of trend line visualizations
Wang, Zesheng
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https://hdl.handle.net/2142/101817
Description
Title
Efficient pattern-based querying of trend line visualizations
Author(s)
Wang, Zesheng
Issue Date
2018-07-12
Director of Research (if dissertation) or Advisor (if thesis)
Parameswaran, Aditya G.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
pattern-based
querying
visual analytics systems
data exploration
Abstract
Finding visualizations with desired patterns is a common goal during data exploration. However, due to the limited expressiveness and flexibility of existing visual analytics systems, pattern-based querying of visualizations has largely been a manual process. We present ShapeSearch, a system that enables users to express their desired patterns using multiple flexible mechanisms—including natural language and visual regular expressions— and automates the search via an optimized execution engine. Internally, the system leverages an expressive ShapeQuery algebra that supports a range of operators and primitives for representing ShapeSearch queries. We will describe how the various components of ShapeSearch help accelerate scientific discovery by automating the search for meaningful patterns in multiple domains such as genomics and material science.
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