کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
563506 | 875499 | 2012 | 6 صفحه PDF | دانلود رایگان |

This paper presents a novel approach for accelerating the popular reciprocal nearest neighbors (RNN) clustering algorithm, i.e. the fast-RNN. We speed up the nearest neighbor chains construction via a novel dynamic slicing strategy for the projection search paradigm. We detail an efficient implementation of the clustering algorithm along with a novel data structure, and present extensive experimental results that illustrate the excellent performance of fast-RNN in low- and high-dimensional spaces. A C++ implementation has been made publicly available.
► We present a fast version of the reciprocal nearest neighbors (RNN) clustering.
► The approach is based on an efficient dynamic space partitioning strategy.
► A novel data structure improves the performance with low- and high-dimensional data.
► Results show that the fast-RNN is faster than the standard RNN.
► A C++ implementation of the algorithm has been made publicly available.
Journal: Signal Processing - Volume 92, Issue 1, January 2012, Pages 270–275