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Indexing Land Surface for Efficient kNN Query

Summary: Proposes the Surface Index R-tree (SIR-tree) with Tight Surface Index (TSI) and Loose Surface Index (LSI) to support exact skNN on land surfaces. Supports a priori-k-free, incremental search with localized pruning, reporting exact shortest surface paths and outperforming baselines in efficiency and accuracy on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9734
Venue
VLDB
Year
2008
Pagerank
0.00011582099
Overall Rank
1,512 | 89.50%
DOI
-

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Showing 6 of 6 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 0.0032118946
48 Nearest Neighbor Queries 1995 SIGMOD 0.0006954126
391 Query Processing in Spatial Network Databases 2003 VLDB 0.00024560891
595 Influence Sets Based on Reverse Nearest Neighbor Queries 2000 SIGMOD 0.00019459302
597 Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases 2004 VLDB 0.00019450818
1,272 Continuous Nearest Neighbor Search 2002 VLDB 0.00012871443
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