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An in memory M-Tree optimized for high-dimensional machine learning applications.

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Supercluster.MTree

An in memory M-Tree optimized for high-dimensional machine learning applications.

References

  1. P. Ciaccia, M. Patella, and P. Zezula. M-tree: an efficient access method for similarity search in metric spaces. In Proceedings of the 23rd International Conference on Very Large Data Bases (VLDB), pages 426–435, Athens, Greece, August 1997.
  2. Samet H. Foundations Of Multidimensional and Metric Data Structures. Amsterdam: Elsevier/Morgan Kaufmann; 2006.
  3. Zezula P. Similarity Search: the Metric Space Approach. New York: Springer; 2006.
  4. G. R. Hjaltason and H. Samet. Incremental similarity search in multimedia databases. Computer Science Technical Report TR–4199, University of Maryland, College Park, MD, November 2000.

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An in memory M-Tree optimized for high-dimensional machine learning applications.

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