---
_id: '46358'
abstract:
- lang: eng
  text: Analysing streaming data has received considerable attention over the recent
    years. A key research area in this field is stream clustering which aims to recognize
    patterns in a possibly unbounded data stream of varying speed and structure. Over
    the past decades a multitude of new stream clustering algorithms have been proposed.
    However, to the best of our knowledge, no rigorous analysis and comparison of
    the different approaches has been performed. Our paper fills this gap and provides
    extensive experiments for a total of ten popular algorithms. We utilize a number
    of standard data sets of both, real and synthetic data and identify key weaknesses
    and strengths of the existing algorithms.
author:
- first_name: Matthias
  full_name: Carnein, Matthias
  last_name: Carnein
- first_name: Dennis
  full_name: Assenmacher, Dennis
  last_name: Assenmacher
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
citation:
  ama: 'Carnein M, Assenmacher D, Trautmann H. An Empirical Comparison of Stream Clustering
    Algorithms. In: <i>Proceedings of the ACM International Conference on Computing
    Frontiers (CF ’17)</i>. ; 2017:361–365. doi:<a href="https://doi.org/10.1145/3075564.3078887">10.1145/3075564.3078887</a>'
  apa: Carnein, M., Assenmacher, D., &#38; Trautmann, H. (2017). An Empirical Comparison
    of Stream Clustering Algorithms. <i>Proceedings of the ACM International Conference
    on Computing Frontiers (CF ’17)</i>, 361–365. <a href="https://doi.org/10.1145/3075564.3078887">https://doi.org/10.1145/3075564.3078887</a>
  bibtex: '@inproceedings{Carnein_Assenmacher_Trautmann_2017, place={Siena, Italy},
    title={An Empirical Comparison of Stream Clustering Algorithms}, DOI={<a href="https://doi.org/10.1145/3075564.3078887">10.1145/3075564.3078887</a>},
    booktitle={Proceedings of the ACM International Conference on Computing Frontiers
    (CF ’17)}, author={Carnein, Matthias and Assenmacher, Dennis and Trautmann, Heike},
    year={2017}, pages={361–365} }'
  chicago: Carnein, Matthias, Dennis Assenmacher, and Heike Trautmann. “An Empirical
    Comparison of Stream Clustering Algorithms.” In <i>Proceedings of the ACM International
    Conference on Computing Frontiers (CF ’17)</i>, 361–365. Siena, Italy, 2017. <a
    href="https://doi.org/10.1145/3075564.3078887">https://doi.org/10.1145/3075564.3078887</a>.
  ieee: 'M. Carnein, D. Assenmacher, and H. Trautmann, “An Empirical Comparison of
    Stream Clustering Algorithms,” in <i>Proceedings of the ACM International Conference
    on Computing Frontiers (CF ’17)</i>, 2017, pp. 361–365, doi: <a href="https://doi.org/10.1145/3075564.3078887">10.1145/3075564.3078887</a>.'
  mla: Carnein, Matthias, et al. “An Empirical Comparison of Stream Clustering Algorithms.”
    <i>Proceedings of the ACM International Conference on Computing Frontiers (CF
    ’17)</i>, 2017, pp. 361–365, doi:<a href="https://doi.org/10.1145/3075564.3078887">10.1145/3075564.3078887</a>.
  short: 'M. Carnein, D. Assenmacher, H. Trautmann, in: Proceedings of the ACM International
    Conference on Computing Frontiers (CF ’17), Siena, Italy, 2017, pp. 361–365.'
date_created: 2023-08-04T15:04:09Z
date_updated: 2023-10-16T13:35:59Z
department:
- _id: '34'
- _id: '819'
doi: 10.1145/3075564.3078887
language:
- iso: eng
page: 361–365
place: Siena, Italy
publication: Proceedings of the ACM International Conference on Computing Frontiers
  (CF ’17)
publication_identifier:
  isbn:
  - 978-1-4503-4487-6/17/05
status: public
title: An Empirical Comparison of Stream Clustering Algorithms
type: conference
user_id: '15504'
year: '2017'
...