ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"
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Abstract (arXiv)
This paper documents the release of the ELKI data mining framework, version 0.7.5. ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions of additional methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms. We will first outline the motivation for this release, the plans for the future, and then give a brief overview over the new functionality in this version. We also include an appendix presenting an overview on the overall implemented functionality.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Feb 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 4; 2024: 1; 2025: 3.
10 papers.
- 2023Unsupervised anomaly detection algorithms on real-world data: how many do we need?cited by 20
- 2021A Triangle Inequality for Cosine Similaritycited by 13
- 2021Accelerating Spherical k-Meanscited by 5
- 2025AI-Generated Compromises for Coalition Formationcited by 3
- 2023Natural Language-Based Synthetic Data Generation for Cluster Analysiscited by 2
- 2024Outlier Detection with Cluster Catch Digraphscited by 2
- 2023Data Aggregation for Hierarchical Clusteringcited by 1
- 2023Sparse Partitioning Around Medoidscited by 0
- 2025Outlyingness Scores with Cluster Catch Digraphscited by 0
- 2025AI-Generated Compromises for Coalition Formation: Modeling, Simulation, and a Textual Case Studycited by 0
- 2025AI-Generated Compromises for Coalition Formation: Modeling, Simulation, and a Textual Case Study27 Nov 2025
- 2025AI-Generated Compromises for Coalition Formation7 Jun 2025
- 2025Outlyingness Scores with Cluster Catch Digraphs9 Jan 2025
- 2024Outlier Detection with Cluster Catch Digraphs17 Sep 2024
- 2023Sparse Partitioning Around Medoids5 Sep 2023
- 2023Data Aggregation for Hierarchical Clustering5 Sep 2023
- 2023Unsupervised anomaly detection algorithms on real-world data: how many do we need?1 May 2023
- 2023Natural Language-Based Synthetic Data Generation for Cluster Analysis24 Mar 2023
- 2021Accelerating Spherical k-Means8 Jul 2021
- 2021A Triangle Inequality for Cosine Similarity8 Jul 2021