iRangeGraph: Improvising Range-dedicated Graphs for Range-filtering Nearest Neighbor Search
Summary: iRangeGraph targets RFANN by materializing a compact set of elemental graphs. A query-time algorithm builds a tailored index for any range from these graphs with low construction cost; experiments show moderate space and robust performance. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yuexuan Xu (Nanyang Technological University)
- 2. Jianyang Gao (Nanyang Technological University)
- 3. Yutong Gou (Nanyang Technological University)
- 4. Cheng Long (Nanyang Technological University)
- 5. Christian S. Jensen (Aalborg University)
BibTeX Citation
@inproceedings{xu_sigmod24,
title = {{iRangeGraph: Improvising Range-dedicated Graphs for Range-filtering Nearest Neighbor Search}},
author = {Xu, Yuexuan and Gao, Jianyang and Gou, Yutong and Long, Cheng and Jensen, Christian S.},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3698814},
url = {https://dl.acm.org/doi/10.1145/3698814},
year = {2024}
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