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Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph

Summary: Introduces MRNG, a low-degree monotonic graph with near-logarithmic ANNS search. Its practical approximation, NSG, jointly preserves connectivity, short paths, and compact indexing, enabling billion-scale deployment and outperforming prior graph methods. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12167
Venue
VLDB
Year
2019
Pagerank
0.00034701237
Overall Rank
93 | 99.37%
DOI
10.14778/3303753.3303754

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{fu_vldb19,
        title = {{Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph}},
        author = {Fu, Cong and Xiang, Chao and Wang, Changxu and Cai, Deng},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {5},
        pages = {461--474},
        doi = {10.14778/3303753.3303754},
        url = {https://doi.org/10.14778/3303753.3303754},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 24 of 124 citing papers.

Rank Citing Paper Year Venue Pagerank
10,417 WoW: A Window-to-Window Incremental Index for Range-Filtering Approximate Nearest Neighbor Search 2026 SIGMOD 5.093636e-05
10,430 Honeybee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning 2026 SIGMOD 5.093636e-05
10,439 Curator: Efficient Vector Search with Low-Selectivity Filters 2026 SIGMOD 5.093636e-05
10,443 Distribution-Aware Exploration for Adaptive HNSW Search 2026 SIGMOD 5.093636e-05
10,447 Efficient and Robust Out-Of-Distribution Vector Similarity Search with Cross-Distribution Monotonic Graph 2026 SIGMOD 5.093636e-05
10,449 Efficient Vector Index Merging in Vector Databases 2026 SIGMOD 5.093636e-05
10,454 Fast-Convergent Proximity Graphs for Approximate Nearest Neighbor Search 2026 SIGMOD 5.093636e-05
10,455 FGIM: a Fast Graph-based Indexes Merging Framework for Approximate Nearest Neighbor Search 2026 SIGMOD 5.093636e-05
10,490 RAIRS: Optimizing Redundant Assignment and List Layout for IVF-Based ANN Search 2026 SIGMOD 5.093636e-05
10,493 Reveal Hidden Pitfalls and Navigate Next Generation of Vector Similarity Search from Task-Centric Views: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,512 SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search 2026 VLDB 5.093636e-05
10,525 Quantization Meets Projection: A Happy Marriage for Approximate k-Nearest Neighbor Search 2026 VLDB 5.093636e-05
10,544 I/O Optimizations for Graph-Based Disk-Resident Approximate Nearest Neighbor Search: A Design Space Exploration 2026 VLDB 5.093636e-05
10,548 JHQ: Johnson-Lindenstrauss Enhanced Hierarchical Quantization for High-Dimensional Approximate Nearest Neighbor Search 2026 VLDB 5.093636e-05
10,563 Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search 2026 VLDB 5.093636e-05
10,571 An Experimental Evaluation of Hybrid Querying on Vectors 2026 VLDB 5.093636e-05
10,585 RED-ANNS: An RDMA-Enabled Distributed Framework for Graph-Based Approximate Nearest Neighbor Search 2026 VLDB 5.093636e-05
10,601 Elastic Index Selection for Label-Hybrid AKNN Search 2026 VLDB 5.093636e-05
10,832 Unleashing Graph Partitioning for Large-Scale Nearest Neighbor Search 2025 VLDB 5.093636e-05
11,005 GaussDB-Vector: A Large-Scale Persistent Real-Time Vector Database for LLM Applications 2025 VLDB 5.093636e-05
11,192 Atom: An Efficient Query Serving System for Embedding-based Knowledge Graph Reasoning with Operator-level Batching 2024 SIGMOD 5.093636e-05
11,255 Blocker and Matcher Can Mutually Benefit: A Co-Learning Framework for Low-Resource Entity Resolution 2024 VLDB 5.093636e-05
11,285 Complex-Path: Effective and Efficient Node Ranking with Paths in Billion-Scale Heterogeneous Graphs 2024 VLDB 5.093636e-05
11,732 MP-RW-LSH: An Efficient Multi-Probe LSH Solution to ANNS-L1 2021 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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