Self-Adaptive Anytime Stream Clustering

@article{Kranen2009SelfAdaptiveAS,
  title={Self-Adaptive Anytime Stream Clustering},
  author={Philipp Kranen and Ira Assent and Corinna Baldauf and Thomas Seidl},
  journal={2009 Ninth IEEE International Conference on Data Mining},
  year={2009},
  pages={249-258}
}
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited. Clustering has to be performed in a single pass over the incoming data and within the possibly varying inter-arrival times of the stream. Likewise, memory is limited, making it impossible to store all data. For clustering, we are faced with the challenge of maintaining a current result that can be presented to the… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 35 CITATIONS, ESTIMATED 40% COVERAGE

88 Citations

01020'11'13'15'17'19
Citations per Year
Semantic Scholar estimates that this publication has 88 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…