Beyond Shortest Paths: Node Fairness in Route Recommendation
Summary: Proposes Rawlsian max–min individual fairness for route recommendation via randomized path distributions that maximize the minimum probability of any eligible node being visited. Key ideas: forward paths (near-shortest alternatives), DAG extraction in single shortest-path time, and a flow/LP-based polynomial solver to compute fair distributions at million-node scale. (summarized by gpt-5-mini on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,588 | Keyword-aware Optimal Route Search | 2012 | VLDB | 6.9428691e-05 |
| 4,621 | Diversified Top-k Route Planning in Road Network | 2022 | VLDB | 6.0426586e-05 |
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