EDA4SUM: Guided Exploration of Data Summaries
Summary: EDA4Sum: guided multi-step data summarization for very large datasets, leveraging EDA to build connected summaries with cumulative utility. Produces k uniform, collectively diverse sets; tunable weights for uniformity, diversity, and novelty; shows multi-step superiority over single-step with expert guidance. (summarized by gpt-5-nano on Feb 09 2026)
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Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,219 | Intelligent Agents for Data Exploration | 2024 | VLDB | 4.3702863e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,993 | Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning | 2020 | SIGMOD | 9.8453334e-05 |
| 4,565 | Constructing and Exploring Composite Items | 2010 | SIGMOD | 6.081125e-05 |
| 4,614 | Interactive Summarization and Exploration of Top Aggregate Query Answers | 2018 | VLDB | 6.0467204e-05 |
| 5,472 | Guided Exploration of User Groups | 2020 | VLDB | 5.4888146e-05 |
| 7,222 | Guided Exploration of Data Summaries | 2022 | VLDB | 4.797186e-05 |
| 11,474 | Exploring Ratings in Subjective Databases | 2021 | SIGMOD | 4.1945683e-05 |
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