Top-k Sorting Under Partial Order Information
Summary: Top-k sorting under partial orders with crowdsourced comparisons; minimizes expert workload. A dedicated top-k algorithm for PO, valid under two notions of the comparator, improving learning-to-rank with synthetic and real data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Eyal Dushkin
- 2. Tova Milo
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,535 | Interactive Graph Search | 2019 | SIGMOD | 4.7178467e-05 |
| 9,678 | Interactive Graph Search for Multiple Targets on DAGs | 2025 | VLDB | 4.3047774e-05 |
| 9,683 | Hierarchical Entity Resolution using an Oracle | 2022 | SIGMOD | 4.3047774e-05 |
| 9,684 | How to Design Robust Algorithms using Noisy Comparison Oracle | 2021 | VLDB | 4.3047774e-05 |
| 10,923 | k-Clustering with Comparison and Distance Oracles | 2024 | PODS | 4.1945683e-05 |
| 11,040 | Robust Best Point Selection under Unreliable User Feedback | 2024 | VLDB | 4.1945683e-05 |
| 11,507 | TQEL: Framework for Query-Driven Linking of Top-K Entities in Social Media Blogs | 2021 | 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 |
|---|---|---|---|---|
| 805 | Evaluating Top-k Selection Queries | 1999 | VLDB | 0.00016437265 |
| 859 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00015870894 |
| 1,609 | A Unified Approach to Ranking in Probabilistic Databases | 2009 | VLDB | 0.00011150935 |
| 1,716 | Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing | 2014 | VLDB | 0.00010795718 |
| 1,992 | Probabilistic Ranking of Database Query Results | 2004 | VLDB | 9.8462684e-05 |
| 4,451 | CLAMShell: Speeding up Crowds for Low-latency Data Labeling | 2016 | VLDB | 6.1738675e-05 |
| 4,579 | Crowdsourced Top-k Algorithms: An Experimental Evaluation | 2016 | VLDB | 6.070469e-05 |
| 5,029 | Crowdsourced Top-k Queries by Confidence-Aware Pairwise Judgments | 2017 | SIGMOD | 5.7502622e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,387 | Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings | 2018 | VLDB | 5.0851965e-05 |
| 2,366 | Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data | 2007 | VLDB | 8.9523637e-05 |
| 11,825 | Efficient Top-k Indexing via General Reductions | 2016 | PODS | 4.1945683e-05 |
| 7,276 | Efficient and Generic Evaluation of Ranked Queries | 2011 | SIGMOD | 4.7798595e-05 |
| 11,810 | A Confidence-Aware Top-k Query Processing Toolkit on Crowdsourcing | 2017 | VLDB | 4.1945683e-05 |
| 12,111 | Optimal Top-k Generation of Attribute Combinations based on Ranked Lists | 2012 | SIGMOD | 4.1945683e-05 |
| 7,135 | Anytime Measures for Top-k Algorithms | 2007 | VLDB | 4.8221884e-05 |
| 7,963 | Efficient Top-K Processing Over Query-Dependent Functions | 2008 | VLDB | 4.613363e-05 |
| 11,707 | A Rating-Ranking Method for Crowdsourced Top-k Computation | 2018 | SIGMOD | 4.1945683e-05 |
| 4,579 | Crowdsourced Top-k Algorithms: An Experimental Evaluation | 2016 | VLDB | 6.070469e-05 |