.png){kind=icon}
.png){kind=icon}
Return
Interactive Data Exploration with Smart Drill-Down
.png){kind=icon}
OA
AI
DOI：10.1109/TKDE.2017.2685998.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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,*, 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.
Keywords:
Data exploration
data summarization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10.4
Papers:
6.7K
Citations:
3.2W
