Analyzing Big Data with Dynamic Quantum Clustering

@article{Weinstein2013AnalyzingBD,
  title={Analyzing Big Data with Dynamic Quantum Clustering},
  author={Marvin Weinstein and Florian Meirer and A. Hume and Ph. Sciau and G. Shaked and Roland Hofstetter and Erez Persi and A. Mehta and David Horn},
  journal={CoRR},
  year={2013},
  volume={abs/1310.2700}
}
How does one search for a needle in a multi-dimensional haystack without knowing what a needle is and without knowing if there is one in the haystack? This kind of problem requires a paradigm shift away from hypothesis driven searches of the data towards a methodology that lets the data speak for itself. Dynamic Quantum Clustering (DQC) is such a methodology. DQC is a powerful visual method that works with big, high-dimensional data. It exploits variations of the density of the data (in feature… CONTINUE READING
Highly Cited
This paper has 17 citations. REVIEW CITATIONS
Tweets
This paper has been referenced on Twitter 23 times. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-6 of 6 references

Synchrotron Radiat

  • F. Meirer, J. Cabana, Y. Liu, A. Mehta, J. C. Andrews, J. P. Pianetta
  • 2012
2 Excerpts

Seismic observations of the 22/11/1995

  • A. Hofstetter
  • Gulf of Aqaba earthquake sequence. Tectonophysics…
  • 2003
1 Excerpt

Source mechanism of the 22/11/1995 Gulf of Aqaba earthquake and its aftershock sequence

  • A. Hofstetter, Thio, H.-K, G. Shamir
  • Journal of Seismology,
  • 2003
2 Excerpts

Source parameters and scaling relationships of earthquakes in Israel

  • A. Shapira, A. Hofstetter
  • 1993
1 Excerpt

Free software helps maps and display data

  • P. Wessel, W. Smith
  • EOS Trans. AGU
  • 1991
1 Excerpt