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Title:Efficient pattern-based querying of trend line visualizations
Author(s):Wang, Zesheng
Advisor(s):Parameswaran, Aditya G.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(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.
Issue Date:2018-07-12
Rights Information:Copyright 2018 Zesheng Wang
Date Available in IDEALS:2018-09-27
Date Deposited:2018-08

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