Interactive Cleaning for Progressive Visualization through Composite Questions
Yuyu Luo, Chengliang Chai, Xuedi Qin, Nan Tang, Guoliang Li
Abstract
In this paper, we study the problem of interactive cleaning for progressive visualization (ICPV): Given a bad visualization V , it is to obtain a "cleaned" visualization V whose distance is far from V , under a given (small) budget w.r.t. human cost. In ICPV, a system interacts with a user iteratively. During each iteration, it asks the user a data cleaning question such as "how to clean detected errors x?", and takes value updates from the user to clean V . Conventional wisdom typically picks a single question (e.g., "Are SIGMOD conference and SIGMOD the same?") with the maximum expected benefit in each iteration. We propose to use a composite question - i.e., a group of single questions to be treated as one question - in each iteration (for example, Are SIGMOD conference in t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and SIGMOD in t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> the same value, and are t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and t <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> duplicates?). A composite question is presented to the user as a small connected graph through a novel GUI that the user can directly operate on. We propose algorithms to select the best composite question in each iteration. Experiments on real-world datasets verify that composite questions are more effective than asking single questions in isolation w.r.t. the human cost.