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.
"A Greedy Clustering Algorithm Based on Interval Pattern Concepts and the Problem of Optimal Box Positioning." J. Appl. Math. 2017 1 - 9, 2017. https://doi.org/10.1155/2017/4323590