Abstract
We present smart drill-down, an operator for interactively exploring a relational table to discover and summarize 'interesting' groups of tuples. Each group of tuples is described by a rule. For instance, the rule (a, b, \star, 1000) tells us that there are 1,000 tuples with value a in the first column and b in the second column (and any value in the third column). Smart drill-down presents an analyst with a list of rules that together describe interesting aspects of the table. The analyst can tailor the definition of interesting, and can interactively apply smart drill-down on an existing rule to explore that part of the table. We demonstrate that the underlying optimization problems are NP-Hard, and describe an algorithm for finding the approximately optimal list of rules to display when the user uses a smart drill-down, and a dynamic sampling scheme for efficiently interacting with large tables. Finally, we perform experiments on real datasets on our experimental prototype to demonstrate the usefulness of smart drill-down and study the performance of our algorithms.
| Original language | English (US) |
|---|---|
| Article number | 7885129 |
| Pages (from-to) | 46-60 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Knowledge and Data Engineering |
| Volume | 31 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2019 |
Keywords
- Data exploration
- data summarization
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications
- Computational Theory and Mathematics