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Efficient Approximation Framework for Attribute Recommendation
Summary: General approximation framework for top-k attribute recommendation in OLAP trend analysis; supports diverse metrics beyond fixed pairs (e.g., KS-test, Chebyshev, EMD, Euclidean). Bounds-based estimation with theoretical guarantees enables fast approximate top-k queries, yielding up to 10x speedups and high accuracy on four real datasets vs TopKAttr.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6741
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 4.1945683e-05
- Overall Rank
- 11,217 | 21.97%
- DOI
-
10.1145/3626726
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| Rank |
Citing Paper |
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Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 22 of 22 cited papers.
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Year |
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| 46 |
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1986 |
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0.00070894702 |
| 167 |
The Snowflake Elastic Data Warehouse |
2016 |
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0.00039180521 |
| 426 |
Amazon Redshift and the Case for Simpler Data Warehouses |
2015 |
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0.00023594359 |
| 460 |
SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics |
2015 |
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0.00022516069 |
| 473 |
Sampling Large Databases for Association Rules |
1996 |
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0.0002233798 |
| 858 |
Efficient Transaction Processing in SAP HANA Database – The End of a Column Store Myth |
2012 |
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0.000158756 |
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2006 |
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0.00014264992 |
| 1,137 |
User-adaptive exploration of multidimensional data |
2000 |
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0.00013730532 |
| 1,204 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
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0.00013319541 |
| 1,353 |
Data Warehouse Configuration |
1997 |
VLDB |
0.00012410919 |
| 1,795 |
MonetDB/XQuery: A Fast XQuery Processor Powered by a Relational Engine |
2006 |
SIGMOD |
0.00010526672 |
| 1,833 |
Data Wrangling: The Challenging Journey from the Wild to the Lake |
2015 |
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0.00010378976 |
| 1,918 |
VizDeck: Self-Organizing Dashboards for Visual Analytics |
2012 |
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0.00010097599 |
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HubPPR: Effective Indexing for Approximate Personalized PageRank |
2017 |
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9.218875e-05 |
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Azure Data Lake Store: A Hyperscale Distributed File Service for Big Data Analytics |
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7.6717218e-05 |
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AnalyticDB: Real-time OLAP Database System at Alibaba Cloud |
2019 |
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7.4711766e-05 |
| 3,653 |
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6.8743355e-05 |
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6.0846728e-05 |
| 5,655 |
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5.387631e-05 |
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4.6179608e-05 |
| 8,228 |
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data |
2007 |
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