Interactive Summarization and Exploration of Top Aggregate Query Answers

TL;DR

This paper introduces an interactive system for summarizing and exploring top aggregate query answers through diverse clustering, parameter customization, and visualization, enhancing user understanding of large answer sets.

Contribution

It proposes a novel interactive framework with optimization algorithms for diverse, customizable clustering of high-valued query answers, supported by experimental evaluation and user studies.

Findings

Effective clustering of top query answers demonstrated

User interface facilitates parameter exploration and visualization

System improves understanding of large answer sets

Abstract

We present a system for summarization and interactive exploration of high-valued aggregate query answers to make a large set of possible answers more informative to the user. Our system outputs a set of clusters on the high-valued query answers showing their common properties such that the clusters are diverse as much as possible to avoid repeating information, and cover a certain number of top original answers as indicated by the user. Further, the system facilitates interactive exploration of the query answers by helping the user (i) choose combinations of parameters for clustering, (ii) inspect the clusters as well as the elements they contain, and (iii) visualize how changes in parameters affect clustering. We define optimization problems, study their complexity, explore properties of the solutions investigating the semi-lattice structure on the clusters, and propose efficient algorithms and optimizations to achieve these goals. We evaluate our techniques experimentally and discuss our prototype with a graphical user interface that facilitates this interactive exploration. A user study is conducted to evaluate the usability of our approach.