Learning User Preferences By Adaptive Pairwise Comparison
Summary: Adaptive pairwise comparison framework for learning user-specific preferences over multi-attribute objects; combines estimation with binary-search-based selection. Introduces orthogonal queries and an S-tree index for fast, interactive evaluation, outperforming baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Li Qian
- 2. Jinyang Gao
- 3. H. V. Jagadish
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,387 | Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings | 2018 | VLDB | 5.0851965e-05 |
| 7,002 | Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size | 2021 | SIGMOD | 4.8670742e-05 |
| 7,559 | Strongly Truthful Interactive Regret Minimization | 2019 | SIGMOD | 4.7107487e-05 |
| 8,388 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 4.5297787e-05 |
| 8,877 | Creating Top Ranking Options in the Continuous Option and Preference Space | 2019 | VLDB | 4.4302563e-05 |
| 9,774 | On m-Impact Regions and Standing Top-k Influence Problems | 2021 | SIGMOD | 4.2856106e-05 |
| 9,775 | Interactive Search for One of the Top-k | 2021 | SIGMOD | 4.2856106e-05 |
| 11,040 | Robust Best Point Selection under Unreliable User Feedback | 2024 | VLDB | 4.1945683e-05 |
| 11,195 | rkHit: Representative Query with Uncertain Preference | 2023 | SIGMOD | 4.1945683e-05 |
| 11,378 | Interactive Mining with Ordered and Unordered Attributes | 2022 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0032169493 |
| 6 | The R*-tree: An Efficient and Robust Access Method for Points and Rectangles | 1990 | SIGMOD | 0.0016162015 |
| 91 | M-tree: An Efficient Access Method for Similarity Search in Metric Spaces | 1997 | VLDB | 0.0005181666 |
| 465 | PREFER: A System for the Efficient Execution of Multiparametric Ranked Queries | 2001 | SIGMOD | 0.00022455702 |
| 707 | Foundations of Preferences in Database Systems | 2002 | VLDB | 0.00017782998 |
| 1,030 | Preference SQL - Design, Implementation, Experiences | 2002 | VLDB | 0.00014557349 |
| 1,080 | A Framework for Expressing and Combining Preferences | 2000 | SIGMOD | 0.00014217619 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,812 | A Practical Theory of Generalization in Selectivity Learning | 2025 | VLDB | 4.2783272e-05 |
| 1,080 | A Framework for Expressing and Combining Preferences | 2000 | SIGMOD | 0.00014217619 |
| 465 | PREFER: A System for the Efficient Execution of Multiparametric Ranked Queries | 2001 | SIGMOD | 0.00022455702 |
| 7,457 | Selectivity Functions of Range Queries are Learnable* | 2022 | SIGMOD | 4.7247191e-05 |
| 8,877 | Creating Top Ranking Options in the Continuous Option and Preference Space | 2019 | VLDB | 4.4302563e-05 |
| 13,281 | Supporting Hard Queries over Probabilistic Preferences | 2020 | VLDB | - |
| 8,825 | Determining the Impact Regions of Competing Options in Preference Space | 2017 | SIGMOD | 4.4415078e-05 |
| 12,008 | Generating Top-k Packages via Preference Elicitation | 2014 | VLDB | 4.1945683e-05 |
| 11,040 | Robust Best Point Selection under Unreliable User Feedback | 2024 | VLDB | 4.1945683e-05 |
| 11,378 | Interactive Mining with Ordered and Unordered Attributes | 2022 | VLDB | 4.1945683e-05 |