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Extracting Top-K Insights from Multi-dimensional Data
Summary: Introduces automatic top-k insights from multi-dimensional data via a new 'insight' concept rooted in multi-step aggregations. Offers a scoring function and pruning/ordering/cube-sharing framework to compute top-k insights efficiently.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5288
- Venue
- SIGMOD
- Year
- 2017
- Pagerank
- 6.9870745e-05
- Overall Rank
- 3,546 | 75.34%
- DOI
-
10.1145/3035918.3035922
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 5,217 |
QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data |
2019 |
SIGMOD |
5.6227959e-05 |
| 5,981 |
DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python |
2021 |
SIGMOD |
5.2448986e-05 |
| 6,514 |
Spade: A Modular Framework for Analytical Exploration of RDF Graphs |
2019 |
VLDB |
5.0321577e-05 |
| 8,388 |
FEDEX: An Explainability Framework for Data Exploration Steps |
2022 |
VLDB |
4.5297787e-05 |
| 8,862 |
TabEE: Tabular Embeddings Explanations |
2024 |
SIGMOD |
4.4331977e-05 |
| 8,996 |
MetaInsight: Automatic Discovery of Structured Knowledge for Exploratory Data Analysis |
2021 |
SIGMOD |
4.4124959e-05 |
| 9,035 |
Data-Driven Insight Synthesis for Multi-Dimensional Data |
2024 |
VLDB |
4.4039656e-05 |
| 9,175 |
Efficient Exploration of Interesting Aggregates in RDF Graphs |
2021 |
SIGMOD |
4.383548e-05 |
| 10,015 |
Differentially Private Explanations for Clusters |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,393 |
SHARQ: Explainability Framework for Association Rules on Relational Data |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,740 |
Finding Convincing Views to Endorse a Claim |
2025 |
VLDB |
4.1945683e-05 |
| 10,784 |
Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models |
2025 |
VLDB |
4.1945683e-05 |
| 11,384 |
BABOONS: Black-Box Optimization of Data Summaries in Natural Language |
2022 |
VLDB |
4.1945683e-05 |
| 11,568 |
Interactive View Recommendation |
2020 |
SIGMOD |
4.1945683e-05 |
| 11,655 |
Top-k Queries over Digital Traces |
2019 |
SIGMOD |
4.1945683e-05 |
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.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 404 |
Multi-Core, Main-Memory Joins: Sort vs. Hash Revisited |
2014 |
VLDB |
0.00024143076 |
| 460 |
SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics |
2015 |
VLDB |
0.00022516069 |
| 472 |
Bottom-Up Computation of Sparse and Iceberg CUBEs |
1999 |
SIGMOD |
0.00022346384 |
| 597 |
Computing Iceberg Queries Efficiently |
1998 |
VLDB |
0.00019475592 |
| 767 |
Explaining differences in multidimensional aggregates |
1999 |
VLDB |
0.00016981309 |
| 1,137 |
User-adaptive exploration of multidimensional data |
2000 |
VLDB |
0.00013730532 |
| 1,552 |
Overview of Data Exploration Techniques |
2015 |
SIGMOD |
0.00011408814 |
| 2,610 |
i3: Intelligent, Interactive Investigation of OLAP data cubes |
2000 |
SIGMOD |
8.4571036e-05 |
| 2,794 |
Towards Keyword-Driven Analytical Processing |
2007 |
SIGMOD |
8.1140341e-05 |
| 3,030 |
DADA: A Data Cube for Dominant Relationship Analysis |
2006 |
SIGMOD |
7.6794959e-05 |
| 3,070 |
Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration |
2014 |
SIGMOD |
7.6137064e-05 |
| 3,819 |
Promotion Analysis in Multi-Dimensional Space |
2009 |
VLDB |
6.7299866e-05 |
| 4,201 |
Meet Charles, big data query advisor |
2013 |
CIDR |
6.3639451e-05 |
| 4,552 |
Outlier Detection for High Dimensional Data |
2001 |
SIGMOD |
6.0922282e-05 |
| 5,987 |
Sampling Cube: A Framework for Statistical OLAP Over Sampling Data |
2008 |
SIGMOD |
5.2432535e-05 |
| 8,507 |
ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes |
2008 |
SIGMOD |
4.4955397e-05 |
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