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 |
|---|---|---|---|---|
| 7,534 | Interactive Graph Search | 2019 | SIGMOD | 4.7133212e-05 |
| 9,678 | Interactive Graph Search for Multiple Targets on DAGs | 2025 | VLDB | 4.3006524e-05 |
| 9,683 | Hierarchical Entity Resolution using an Oracle | 2022 | SIGMOD | 4.3006524e-05 |
| 9,684 | How to Design Robust Algorithms using Noisy Comparison Oracle | 2021 | VLDB | 4.3006524e-05 |
| 10,927 | k-Clustering with Comparison and Distance Oracles | 2024 | PODS | 4.1905499e-05 |
| 11,043 | Robust Best Point Selection under Unreliable User Feedback | 2024 | VLDB | 4.1905499e-05 |
| 11,511 | TQEL: Framework for Query-Driven Linking of Top-K Entities in Social Media Blogs | 2021 | VLDB | 4.1905499e-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 |
|---|---|---|---|---|
| 802 | Evaluating Top-k Selection Queries | 1999 | VLDB | 0.00016440813 |
| 854 | So Who Won? Dynamic Max Discovery with the Crowd | 2012 | SIGMOD | 0.00015879917 |
| 1,612 | A Unified Approach to Ranking in Probabilistic Databases | 2009 | VLDB | 0.00011142757 |
| 1,713 | Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing | 2014 | VLDB | 0.00010785323 |
| 1,996 | Probabilistic Ranking of Database Query Results | 2004 | VLDB | 9.8374939e-05 |
| 4,453 | CLAMShell: Speeding up Crowds for Low-latency Data Labeling | 2016 | VLDB | 6.1690121e-05 |
| 4,580 | Crowdsourced Top-k Algorithms: An Experimental Evaluation | 2016 | VLDB | 6.0646299e-05 |
| 5,029 | Crowdsourced Top-k Queries by Confidence-Aware Pairwise Judgments | 2017 | SIGMOD | 5.7447454e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,378 | Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings | 2018 | VLDB | 5.0844506e-05 |
| 2,371 | Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data | 2007 | VLDB | 8.9443366e-05 |
| 11,833 | Efficient Top-k Indexing via General Reductions | 2016 | PODS | 4.1905499e-05 |
| 7,273 | Efficient and Generic Evaluation of Ranked Queries | 2011 | SIGMOD | 4.775366e-05 |
| 11,818 | A Confidence-Aware Top-k Query Processing Toolkit on Crowdsourcing | 2017 | VLDB | 4.1905499e-05 |
| 12,119 | Optimal Top-k Generation of Attribute Combinations based on Ranked Lists | 2012 | SIGMOD | 4.1905499e-05 |
| 7,133 | Anytime Measures for Top-k Algorithms | 2007 | VLDB | 4.8175888e-05 |
| 7,966 | Efficient Top-K Processing Over Query-Dependent Functions | 2008 | VLDB | 4.6089395e-05 |
| 11,713 | A Rating-Ranking Method for Crowdsourced Top-k Computation | 2018 | SIGMOD | 4.1905499e-05 |
| 4,580 | Crowdsourced Top-k Algorithms: An Experimental Evaluation | 2016 | VLDB | 6.0646299e-05 |