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Expanding Reverse Nearest Neighbors

Summary: ERNN: choose up to k edge weight reductions to maximize a facility's reverse nearest neighbor set; problem is NP-hard, APX-hard, non‑monotone and non‑submodular. Propose greedy heuristics that prune edges and cut per‑edge cost, giving orders‑of‑magnitude speedups and large RNN gains. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13740
Venue
VLDB
Year
2024
Pagerank
4.1945683e-05
Overall Rank
11,141 | 22.50%
DOI
10.14778/3636218.3636220

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