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A Greedy Clustering Algorithm Based on Interval Pattern Concepts and the Problem of Optimal Box Positioning

Author

Listed:
  • Stepan A. Nersisyan
  • Vera V. Pankratieva
  • Vladimir M. Staroverov
  • Vladimir E. Podolskii

Abstract

We consider a clustering approach based on interval pattern concepts. Exact algorithms developed within the framework of this approach are unable to produce a solution for high-dimensional data in a reasonable time, so we propose a fast greedy algorithm which solves the problem in geometrical reformulation and shows a good rate of convergence and adequate accuracy for experimental high-dimensional data. Particularly, the algorithm provided high-quality clustering of tactile frames registered by Medical Tactile Endosurgical Complex.

Suggested Citation

  • Stepan A. Nersisyan & Vera V. Pankratieva & Vladimir M. Staroverov & Vladimir E. Podolskii, 2017. "A Greedy Clustering Algorithm Based on Interval Pattern Concepts and the Problem of Optimal Box Positioning," Journal of Applied Mathematics, Hindawi, vol. 2017, pages 1-9, September.
    • Handle: RePEc:hin:jnljam:4323590
    DOI: 10.1155/2017/4323590
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    Cited by:

    1. Alexei V. Galatenko & Stepan A. Nersisyan & Dmitriy N. Zhuk, 2019. "NP-Hardness of the Problem of Optimal Box Positioning," Mathematics, MDPI, vol. 7(8), pages 1-6, August.

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