Interactive Summarization and Exploration of Top Aggregate Query Answers.

Published

Conference Paper

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.

Full Text

Duke Authors

Cited Authors

  • Wen, Y; Zhu, X; Roy, S; Yang, J

Published Date

  • September 2018

Published In

Volume / Issue

  • 11 / 13

Start / End Page

  • 2196 - 2208

PubMed ID

  • 31179155

Pubmed Central ID

  • 31179155

Electronic International Standard Serial Number (EISSN)

  • 2150-8097

International Standard Serial Number (ISSN)

  • 2150-8097

Digital Object Identifier (DOI)

  • 10.14778/3275366.3284965