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DEG: Efficient Hybrid Vector Search Using the Dynamic Edge Navigation Graph

Summary: DEG is a graph-based ANNS index for hybrid vector search on bimodal data with dynamic alpha in HVQ. It builds a Pareto-frontier neighbor set across alpha, uses dynamic edge pruning with active ranges, and an edge-seed acceleration to speed queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7089
Venue
SIGMOD
Year
2025
Pagerank
5.550467e-05
Overall Rank
7,761 | 46.76%
DOI
10.1145/3709679

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yin_sigmod25,
        title = {{DEG: Efficient Hybrid Vector Search Using the Dynamic Edge Navigation Graph}},
        author = {Yin, Ziqi and Gao, Jianyang and Balsebre, Pasquale and Cong, Gao and Long, Cheng},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709679},
        url = {https://dl.acm.org/doi/10.1145/3709679},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
6,615 A Topology-Aware Localized Update Strategy for Graph-Based ANN Index 2026 VLDB 5.8214312e-05
10,193 An In-Depth Study of Filter-Agnostic Vector Search on a PostgreSQL Database System: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,417 WoW: A Window-to-Window Incremental Index for Range-Filtering Approximate Nearest Neighbor 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
10,525 Quantization Meets Projection: A Happy Marriage for Approximate k-Nearest Neighbor Search 2026 VLDB 5.093636e-05
10,601 Elastic Index Selection for Label-Hybrid AKNN Search 2026 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 cited papers.

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

Rank Cited Paper Year Venue Pagerank
4 The R*-tree: An Efficient and Robust Access Method for Points and Rectangles 1990 SIGMOD 0.001157935
5 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0010828372
46 A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces 1998 VLDB 0.00044853085
93 Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph 2019 VLDB 0.00034701237
286 Milvus: A Purpose-Built Vector Data Management System 2021 SIGMOD 0.00022357911
332 Query-Aware Locality-Sensitive Hashing for Approximate Nearest Neighbor Search 2016 VLDB 0.00020920444
369 Locality-Sensitive Hashing Scheme Based on Dynamic Collision Counting 2012 SIGMOD 0.00019945234
398 A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search 2021 VLDB 0.00019194947
406 AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data 2020 VLDB 0.00019054532
705 HD-Index: Pushing the Scalability-Accuracy Boundary for Approximate kNN Search in High-Dimensional Spaces 2018 VLDB 0.00014829964
926 Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination 2020 SIGMOD 0.00013181732
990 SK-LSH: An Efficient Index Structure for Approximate Nearest Neighbor Search 2014 VLDB 0.00012796562
1,357 RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search 2024 SIGMOD 0.00011043994
1,430 VHP: Approximate Nearest Neighbor Search via Virtual Hypersphere Partitioning 2020 VLDB 0.0001080902
1,589 Manu: A Cloud Native Vector Database Management System 2022 VLDB 0.00010264469
2,010 iDEC: Indexable Distance Estimating Codes for Approximate Nearest Neighbor Search 2020 VLDB 9.3085202e-05
3,279 Locality-Sensitive Hashing Scheme based on Longest Circular Co-Substring 2020 SIGMOD 7.5711218e-05
3,858 A General and Efficient Querying Method for Learning to Hash 2018 SIGMOD 7.067591e-05
11,378 Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword Queries 2023 SIGMOD 5.093636e-05
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