Promotion Analysis in Multi-Dimensional Space
Summary: PromoRank discovers promotive subspaces where a given object is prominent despite weak global rank. It uses subspace pruning, object pruning, and a promotion cube to prune search space and reduce aggregation cost; experiments on two real datasets show gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tianyi Wu
- 2. Dong Xin
- 3. Qiaozhu Mei
- 4. Jiawei Han
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,852 | MRI: Meaningful Interpretations of Collaborative Ratings | 2011 | VLDB | 8.0151391e-05 |
| 3,546 | Extracting Top-K Insights from Multi-dimensional Data | 2017 | SIGMOD | 6.9870745e-05 |
| 5,047 | Identifying the Most Influential Data Objects with Reverse Top-k Queries | 2010 | VLDB | 5.7379554e-05 |
| 5,217 | QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data | 2019 | SIGMOD | 5.6227959e-05 |
| 7,586 | Maverick: Discovering Exceptional Facts from Knowledge Graphs | 2018 | SIGMOD | 4.7036704e-05 |
| 8,548 | WINACS: Construction and Analysis of Web-Based Computer Science Information Networks | 2011 | SIGMOD | 4.4937074e-05 |
| 8,996 | MetaInsight: Automatic Discovery of Structured Knowledge for Exploratory Data Analysis | 2021 | SIGMOD | 4.4124959e-05 |
| 10,740 | Finding Convincing Views to Endorse a Claim | 2025 | VLDB | 4.1945683e-05 |
| 11,384 | BABOONS: Black-Box Optimization of Data Summaries in Natural Language | 2022 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015496097 |
| 273 | Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets | 1999 | SIGMOD | 0.00029390945 |
| 472 | Bottom-Up Computation of Sparse and Iceberg CUBEs | 1999 | SIGMOD | 0.00022346384 |
| 1,258 | Ordering the Attributes of Query Results | 2006 | SIGMOD | 0.00013013676 |
| 1,992 | Probabilistic Ranking of Database Query Results | 2004 | VLDB | 9.8462684e-05 |
| 3,030 | DADA: A Data Cube for Dominant Relationship Analysis | 2006 | SIGMOD | 7.6794959e-05 |
| 6,293 | Ad-Hoc Aggregations of Ranked Lists in the Presence of Hierarchies | 2008 | SIGMOD | 5.1257071e-05 |
| 8,507 | ARCube: Supporting Ranking Aggregate Queries in Partially Materialized Data Cubes | 2008 | SIGMOD | 4.4955397e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,774 | On m-Impact Regions and Standing Top-k Influence Problems | 2021 | SIGMOD | 4.2856106e-05 |
| 2,366 | Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data | 2007 | VLDB | 8.9523637e-05 |
| 3,546 | Extracting Top-K Insights from Multi-dimensional Data | 2017 | SIGMOD | 6.9870745e-05 |
| 4,711 | Answering Top-k Queries with Multi-Dimensional Selections: The Ranking Cube Approach | 2006 | VLDB | 5.9790683e-05 |
| 8,168 | Evaluating Clustering in Subspace Projections of High Dimensional Data | 2009 | VLDB | 4.5701004e-05 |
| 2,019 | Finding Generalized Projected Clusters in High Dimensional Spaces | 2000 | SIGMOD | 9.7707059e-05 |
| 7,009 | Understanding local structure in ranked datasets | 2013 | CIDR | 4.8637193e-05 |
| 6,203 | Maximum Rank Query | 2015 | VLDB | 5.1590738e-05 |
| 8,877 | Creating Top Ranking Options in the Continuous Option and Preference Space | 2019 | VLDB | 4.4302563e-05 |
| 8,825 | Determining the Impact Regions of Competing Options in Preference Space | 2017 | SIGMOD | 4.4415078e-05 |