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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)

Paper ID
12839
Venue
VLDB
Year
2022
Pagerank
4.1905499e-05
Overall Rank
11,396 | 20.80%
DOI
10.14778/3554821.3554851

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
9,222 Intelligent Agents for Data Exploration 2024 VLDB 4.366098e-05
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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
1,992 Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning 2020 SIGMOD 9.8415851e-05
4,561 Constructing and Exploring Composite Items 2010 SIGMOD 6.0758276e-05
4,608 Interactive Summarization and Exploration of Top Aggregate Query Answers 2018 VLDB 6.046643e-05
5,481 Guided Exploration of User Groups 2020 VLDB 5.483544e-05
7,200 Guided Exploration of Data Summaries 2022 VLDB 4.7980895e-05
11,478 Exploring Ratings in Subjective Databases 2021 SIGMOD 4.1905499e-05
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