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Efficient Indexes for Diverse Top-k Range Queries

Summary: Studying top-k range queries that return diverse, high-weight points in R^d under bicriteria (trade-off value vs. diversity) and constrained (maximize value with diversity constraint) objectives; gives offline (0.5-ε)-approx algorithms. Proposes near-linear-size, near-linear-time-built indexes answering rectangle queries in O(k polylog n) with (0.5-ε)-approx; for constrained queries achieves 0.5^{O(d)}-approx or (1-ε)-approx if allowing ε expansion, same query time. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1798
Venue
PODS
Year
2020
Pagerank
4.427232e-05
Overall Rank
8,919 | 37.96%
DOI
10.1145/3375395.3387667

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
10,927 Computing A Well-Representative Summary of Conjunctive Query Results 2024 PODS 4.1945683e-05
10,961 Faster Algorithms for Fair Max-Min Diversification in Rd 2024 SIGMOD 4.1945683e-05
11,218 Equitable Top-k Results for Long Tail Data 2023 SIGMOD 4.1945683e-05
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