DBAIHCJan 7, 2020

Monte Carlo Tree Search for Generating Interactive Data Analysis Interfaces

arXiv:2001.01902v210 citations
AI Analysis

This work aims to democratize data access for end-users by reducing the cost of building customized interfaces, though it is incremental by improving on prior syntactic approaches.

The paper tackles the problem of automatically generating interactive data analysis interfaces from SQL query logs by addressing layout usability and query sequence, proposing Monte Carlo Tree Search to optimize interfaces for ease of expression.

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.

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