Monte Carlo Tree Search for Generating Interactive Data Analysis Interfaces
Video
Team Information
Team Members
Yiru Chen, PhD Student, Department of Computer Science, Columbia University
Faculty Advisor: Eugene Wu, Assistant Professor of Computer Science; and Co-Chair of the Data, Media & Society Center, The Data Science Institute, Columbia University
Abstract
Interactive tools like user interfaces help democratize data access for end-users by hiding underlying programming details and exposing the necessary widget interface to users. Since customized interfaces are costly to build, automated interface generation is desirable. SQL is the dominant way to analyze data and there already exists logs to analyze data. Previous work proposed a syntactic approach to analyze structural changes in SQL query logs and automatically generates a set of widgets to express the changes. However, they do not consider layout usability and the sequential order of queries in the log. We propose to adopt Monte Carlo Tree Search(MCTS) to search for the optimal interface that accounts for hierarchical layout as well as the usability in terms of how easy to express the query log.Contact this Team
Team Contact: Yiru Chen (use form to send email)
