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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
0.00021800242
Overall Rank
300 | 97.99%
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
142 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00029189529
917 Trajectory Clustering: A Partition-and-Group Framework 2007 SIGMOD 0.00013085176
928 A Framework for Clustering Evolving Data Streams 2003 VLDB 0.0001301967
986 DBSCAN Revisited: Mis-Claim, Un-Fixability, and Approximation 2015 SIGMOD 0.00012663024
1,998 Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data 2001 SIGMOD 9.2123795e-05
3,060 Dynamic Density Based Clustering 2017 SIGMOD 7.6928918e-05
3,302 RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning 2018 SIGMOD 7.4403022e-05
3,903 CSV: Visualizing and Mining Cohesive Subgraphs 2008 SIGMOD 6.9307809e-05
4,135 ST2B-tree: A Self-Tunable Spatio-Temporal B+-tree Index for Moving Objects 2008 SIGMOD 6.7843671e-05
4,184 YADING: Fast Clustering of Large-Scale Time Series Data 2015 VLDB 6.7508911e-05
4,454 Parallel Index-Based Structural Graph Clustering and Its Approximation 2021 SIGMOD 6.5915e-05
4,746 Density-based Place Clustering in Geo-Social Networks 2014 SIGMOD 6.4366273e-05
4,974 Computing Clusters of Correlation Connected Objects 2004 SIGMOD 6.3289112e-05
5,421 Theoretically-Efficient and Practical Parallel DBSCAN 2020 SIGMOD 6.1355031e-05
5,990 Fast Euclidean OPTICS with Bounded Precision in Low Dimensional Space 2018 SIGMOD 5.9225209e-05
6,020 The 3W Model and Algebra for Unified Data Mining 2000 VLDB 5.9101772e-05
6,336 Outlier-robust Clustering using Independent Components 2008 SIGMOD 5.8085039e-05
6,564 Mining Significant Semantic Locations From GPS Data 2010 VLDB 5.7450752e-05
7,096 Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods 2025 VLDB 5.5991152e-05
7,098 A New Sparse Data Clustering Method Based On Frequent Items 2023 SIGMOD 5.5991152e-05
7,165 C2P: Clustering based on Closest Pairs 2001 VLDB 5.5931268e-05
7,436 Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering 2004 SIGMOD 5.5264836e-05
7,748 Clustering Objects on a Spatial Network 2004 SIGMOD 5.4587215e-05
8,246 Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms 2024 SIGMOD 5.3680406e-05
8,388 CURLER: Finding and Visualizing Nonlinear Correlation Clusters 2005 SIGMOD 5.3400228e-05
8,904 FINEX: A Fast Index for Exact & Flexible Density-Based Clustering 2023 SIGMOD 5.2534908e-05
9,186 Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering 2001 SIGMOD 5.2100382e-05
9,442 Using Sets of Feature Vectors for Similarity Search on Voxelized CAD Objects 2003 SIGMOD 5.175852e-05
9,455 A Framework for Projected Clustering of High Dimensional Data Streams 2004 VLDB 5.1733617e-05
9,500 Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data 2023 SIGMOD 5.168414e-05
9,630 An Efficient Algorithm for Distance-based Structural Graph Clustering 2023 SIGMOD 5.1469233e-05
10,275 On Saving Outliers for Better Clustering over Noisy Data 2021 SIGMOD 5.0466043e-05
10,759 FB*: A Compact Index for Efficient and Exact Density-based Clustering 2026 VLDB 4.9769913e-05
11,059 Schuyler: Self-Supervised Clustering of Tables in Relational Databases 2026 VLDB 4.9769913e-05
11,063 CLaP - State Detection from Time Series 2026 VLDB 4.9769913e-05
11,288 Evaluating Methods for Efficient Entity Count Estimation 2025 VLDB 4.9769913e-05
11,591 Ensemble Clustering based on Meta-Learning and Hyperparameter Optimization 2024 VLDB 4.9769913e-05
11,740 F3 KM: Federated, Fair, and Fast k-means 2023 SIGMOD 4.9769913e-05
11,974 PyExplore: Query Recommendations for Data Exploration without Query Logs 2021 SIGMOD 4.9769913e-05
11,977 Fast Density-Peaks Clustering: Multicore-based Parallelization Approach 2021 SIGMOD 4.9769913e-05
11,988 Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering* 2021 SIGMOD 4.9769913e-05
12,252 MustaCHE: A Multiple Clustering Hierarchies Explorer 2018 VLDB 4.9769913e-05
13,111 A Shrinking-Based Approach for Multi-Dimensional Data Analysis 2003 VLDB 4.9769913e-05
13,112 Data Bubbles for Non-Vector Data: Speeding-up Hierarchical Clustering in Arbitrary Metric Spaces 2003 VLDB 4.9769913e-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 0.0011402175
32 BIRCH: An Efficient Data Clustering Method for Very Large Databases 1996 SIGMOD 0.00049714561
56 M-tree: An Efficient Access Method for Similarity Search in Metric Spaces 1997 VLDB 0.00040363819
90 The X-tree: An Index Structure for High-Dimensional Data 1996 VLDB 0.00034847854
94 Efficient and Effective Clustering Methods for Spatial Data Mining 1994 VLDB 0.0003456395
308 Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications 1998 SIGMOD 0.00021463972
364 CURE: An Efficient Clustering Algorithm for Large Databases 1998 SIGMOD 0.00019978187
1,946 Incremental Clustering for Mining in a Data Warehousing Environment 1998 VLDB 9.3216771e-05
1,988 WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases 1998 VLDB 9.2470974e-05
5,300 Databases and Visualization 1996 SIGMOD 6.1881158e-05
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