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On m-Impact Regions and Standing Top-k Influence Problems

Summary: Defines m-Impact Regions (mIR) to identify attribute-value regions that place a product in the top-k for a user fraction, enabling targeted marketing and product refinement. Delivers exact, scalable algorithms for standing top-k influence, outperforming heuristics with real-review data experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h3b44d80e2431eec3
Venue
SIGMOD
Year
2021
Pagerank
5.0830849e-05
Overall Rank
10,086 | 32.19%
DOI
10.1145/3448016.3452832

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{tang_sigmod21,
        title = {{On m-Impact Regions and Standing Top-k Influence Problems}},
        author = {Tang, Bo and Mouratidis, Kyriakos and Han, Mingji},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3452832},
        url = {https://dl.acm.org/doi/10.1145/3448016.3452832},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,712 rkHit: Representative Query with Uncertain Preference 2023 SIGMOD 4.9793485e-05
11,874 tau-LevelIndex: Towards Efficient Query Processing in Continuous Preference Space 2022 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 20 of 20 cited papers.

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

Rank Cited Paper Year Venue Pagerank
5 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0010679641
342 The Onion Technique: Indexing for Linear Optimization Queries 2000 SIGMOD 0.00020530255
418 PREFER: A System for the Efficient Execution of Multiparametric Ranked Queries 2001 SIGMOD 0.00018617842
545 Influence Sets Based on Reverse Nearest Neighbor Queries 2000 SIGMOD 0.00016607433
1,087 Regret-Minimizing Representative Databases 2010 VLDB 0.00012097722
2,485 Processing a Large Number of Continuous Preference Top-k Queries 2012 SIGMOD 8.3993865e-05
2,786 DADA: A Data Cube for Dominant Relationship Analysis 2006 SIGMOD 8.0165674e-05
2,955 Answering Why-not Questions on Reverse Top-k Queries 2015 VLDB 7.8102237e-05
4,082 Learning User Preferences By Adaptive Pairwise Comparison 2015 VLDB 6.8176001e-05
4,241 Creating Competitive Products 2009 VLDB 6.7085648e-05
4,547 Identifying the Most Influential Data Objects with Reverse Top-k Queries 2010 VLDB 6.5425744e-05
4,614 Branch-and-Bound Algorithm for Reverse Top-k Queries 2013 SIGMOD 6.5014577e-05
4,831 Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative 2017 SIGMOD 6.3897334e-05
5,068 Efficient k-Regret Query Algorithm with Restriction-free Bound for any Dimensionality 2018 SIGMOD 6.2893698e-05
5,626 Reconciling Skyline and Ranking Queries 2017 VLDB 6.0606965e-05
5,913 Reverse k-Ranks Query 2014 VLDB 5.9500931e-05
6,176 Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings 2018 VLDB 5.8609559e-05
6,378 Maximum Rank Query 2015 VLDB 5.8086918e-05
8,993 Creating Top Ranking Options in the Continuous Option and Preference Space 2019 VLDB 5.2419215e-05
9,172 Determining the Impact Regions of Competing Options in Preference Space 2017 SIGMOD 5.2140475e-05
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