Sum-Max Monotonic Ranked Joins for Evaluating Top-K Twig Queries on Weighted Data Graphs
Summary: Shows structured top-k twig queries on weighted graphs remain NP-hard and violate monotonicity required by ranked joins. Introduces sum-max monotonicity and the horizon-based, self-punctuating HR-Join operator for efficient ranked subresult merging. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yan Qi (Arizona State University)
- 2. K. Selcuk Candan (Arizona State University)
- 3. Maria Luisa Sapino (University of Torino)
BibTeX Citation
@article{qi_vldb07,
title = {{Sum-Max Monotonic Ranked Joins for Evaluating Top-K Twig Queries on Weighted Data Graphs}},
author = {Qi, Yan and Candan, K. Selcuk and Sapino, Maria Luisa},
journal = {PVLDB},
series = {{VLDB} '07},
pages = {507--518},
year = {2007}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,221 | Efficient Algorithms for Exact Ranked Twig-Pattern Matching over Graphs | 2008 | SIGMOD | 6.8233111e-05 |
| 6,412 | Ranked Enumeration of Join Queries with Projections | 2022 | VLDB | 5.8836116e-05 |
| 7,664 | Optimal Enumeration: Efficient Top-k Tree Matching | 2015 | VLDB | 5.5720259e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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