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Guided Exploration of Data Summaries

Summary: Formalizes Eda4Sum: guided, sequential data summarization yielding connected, k-uniform, diverse subsets to maximize cumulative utility. Introduces Top1Sum (greedy per-step) and RLSum (DRL-based policy); experiments on three large datasets show superiority over one-shot and EDA baselines, highlighting scalability and need for domain guidance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12680
Venue
VLDB
Year
2022
Pagerank
4.797186e-05
Overall Rank
7,222 | 49.76%
DOI
10.14778/3538598.3538603

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Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
7,172 Summarized Causal Explanations For Aggregate Views 2024 SIGMOD 4.8114797e-05
8,862 TabEE: Tabular Embeddings Explanations 2024 SIGMOD 4.4331977e-05
9,219 Intelligent Agents for Data Exploration 2024 VLDB 4.3702863e-05
9,644 Fair and Actionable Causal Prescription Ruleset 2025 SIGMOD 4.3109001e-05
10,015 Differentially Private Explanations for Clusters 2026 SIGMOD 4.1945683e-05
10,147 Causal Explanations for Disparate Trends: Where and Why? 2026 SIGMOD 4.1945683e-05
10,152 Data-Semantics-Aware Recommendation of Diverse Pivot Tables 2026 SIGMOD 4.1945683e-05
10,740 Finding Convincing Views to Endorse a Claim 2025 VLDB 4.1945683e-05
10,875 SDEcho: Efficient Explanation of Aggregated Sequence Difference 2025 VLDB 4.1945683e-05
11,394 EDA4SUM: Guided Exploration of Data Summaries 2022 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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