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OPTICS: Ordering Points To Identify the Clustering Structure

Summary: OPTICS builds a density-based cluster-ordering instead of explicit clusters. This ordering reveals intrinsic structure across parameter settings, enabling automatic, interactive discovery and scalable visualization for medium to very large data sets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h5a058097f829b6f4
Venue
SIGMOD
Year
1999
Pagerank
0.00021743411
Overall Rank
300 | 98.00%
DOI
10.1145/304182.304187

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{ankerst_sigmod99,
        title = {{OPTICS: Ordering Points To Identify the Clustering Structure}},
        author = {Ankerst, Mihael and Breunig, Markus M. and Kriegel, Hans-Peter and Sander, Jörg},
        series = {{SIGMOD} '99},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/304182.304187},
        url = {https://dl.acm.org/doi/10.1145/304182.304187},
        year = {1999}
}

Incoming Citations (Sorted by Pagerank)

Showing 44 of 44 citing papers.

Rank Citing Paper Year Venue Pagerank
143 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00029095978
920 Trajectory Clustering: A Partition-and-Group Framework 2007 SIGMOD 0.00013041987
933 A Framework for Clustering Evolving Data Streams 2003 VLDB 0.00012976795
992 DBSCAN Revisited: Mis-Claim, Un-Fixability, and Approximation 2015 SIGMOD 0.00012621584
2,007 Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data 2001 SIGMOD 9.182637e-05
3,070 Dynamic Density Based Clustering 2017 SIGMOD 7.6675081e-05
3,314 RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning 2018 SIGMOD 7.4156999e-05
3,903 CSV: Visualizing and Mining Cohesive Subgraphs 2008 SIGMOD 6.9150978e-05
4,151 ST2B-tree: A Self-Tunable Spatio-Temporal B+-tree Index for Moving Objects 2008 SIGMOD 6.7619457e-05
4,201 YADING: Fast Clustering of Large-Scale Time Series Data 2015 VLDB 6.7286195e-05
4,308 Parallel Index-Based Structural Graph Clustering and Its Approximation 2021 SIGMOD 6.657571e-05
4,739 Density-based Place Clustering in Geo-Social Networks 2014 SIGMOD 6.4295168e-05
5,000 Computing Clusters of Correlation Connected Objects 2004 SIGMOD 6.3080199e-05
5,438 Theoretically-Efficient and Practical Parallel DBSCAN 2020 SIGMOD 6.1152153e-05
6,001 Fast Euclidean OPTICS with Bounded Precision in Low Dimensional Space 2018 SIGMOD 5.9029373e-05
6,034 The 3W Model and Algebra for Unified Data Mining 2000 VLDB 5.8906344e-05
6,347 Outlier-robust Clustering using Independent Components 2008 SIGMOD 5.7893117e-05
6,574 Mining Significant Semantic Locations From GPS Data 2010 VLDB 5.7260784e-05
7,119 Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods 2025 VLDB 5.580601e-05
7,121 A New Sparse Data Clustering Method Based On Frequent Items 2023 SIGMOD 5.580601e-05
7,185 C2P: Clustering based on Closest Pairs 2001 VLDB 5.5746325e-05
7,457 Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering 2004 SIGMOD 5.5082134e-05
7,762 Clustering Objects on a Spatial Network 2004 SIGMOD 5.4406715e-05
8,263 Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms 2024 SIGMOD 5.3502905e-05
8,406 CURLER: Finding and Visualizing Nonlinear Correlation Clusters 2005 SIGMOD 5.3223662e-05
8,924 FINEX: A Fast Index for Exact & Flexible Density-Based Clustering 2023 SIGMOD 5.2361195e-05
9,083 An Efficient Algorithm for Distance-based Structural Graph Clustering 2023 SIGMOD 5.209913e-05
9,211 Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering 2001 SIGMOD 5.1928106e-05
9,466 Using Sets of Feature Vectors for Similarity Search on Voxelized CAD Objects 2003 SIGMOD 5.1590473e-05
9,485 A Framework for Projected Clustering of High Dimensional Data Streams 2004 VLDB 5.1562553e-05
9,529 Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data 2023 SIGMOD 5.151324e-05
10,302 On Saving Outliers for Better Clustering over Noisy Data 2021 SIGMOD 5.0299171e-05
10,820 FB*: A Compact Index for Efficient and Exact Density-based Clustering 2026 VLDB 4.9605343e-05
11,120 Schuyler: Self-Supervised Clustering of Tables in Relational Databases 2026 VLDB 4.9605343e-05
11,124 CLaP - State Detection from Time Series 2026 VLDB 4.9605343e-05
11,344 Evaluating Methods for Efficient Entity Count Estimation 2025 VLDB 4.9605343e-05
11,639 Ensemble Clustering based on Meta-Learning and Hyperparameter Optimization 2024 VLDB 4.9605343e-05
11,784 F3 KM: Federated, Fair, and Fast k-means 2023 SIGMOD 4.9605343e-05
12,018 PyExplore: Query Recommendations for Data Exploration without Query Logs 2021 SIGMOD 4.9605343e-05
12,021 Fast Density-Peaks Clustering: Multicore-based Parallelization Approach 2021 SIGMOD 4.9605343e-05
12,032 Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering* 2021 SIGMOD 4.9605343e-05
12,295 MustaCHE: A Multiple Clustering Hierarchies Explorer 2018 VLDB 4.9605343e-05
13,152 A Shrinking-Based Approach for Multi-Dimensional Data Analysis 2003 VLDB 4.9605343e-05
13,153 Data Bubbles for Non-Vector Data: Speeding-up Hierarchical Clustering in Arbitrary Metric Spaces 2003 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 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 0.0011386412
32 BIRCH: An Efficient Data Clustering Method for Very Large Databases 1996 SIGMOD 0.00049559562
56 M-tree: An Efficient Access Method for Similarity Search in Metric Spaces 1997 VLDB 0.0004024707
90 The X-tree: An Index Structure for High-Dimensional Data 1996 VLDB 0.00034749222
94 Efficient and Effective Clustering Methods for Spatial Data Mining 1994 VLDB 0.00034470298
310 Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications 1998 SIGMOD 0.00021410542
364 CURE: An Efficient Clustering Algorithm for Large Databases 1998 SIGMOD 0.00019916561
1,948 Incremental Clustering for Mining in a Data Warehousing Environment 1998 VLDB 9.30382e-05
1,996 WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases 1998 VLDB 9.2175908e-05
5,314 Databases and Visualization 1996 SIGMOD 6.1685016e-05
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