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Open AccessArticle

A Fast Algorithm for Identifying Density-Based Clustering Structures Using a Constraint Graph

1
Department of Computer Science, Chungbuk National University, Cheongju 28644, Korea
2
Department of Software, Gachon University, Seongnam 13120, Korea
*
Authors to whom correspondence should be addressed.
Electronics 2019, 8(10), 1094; https://doi.org/10.3390/electronics8101094
Received: 2 August 2019 / Revised: 12 September 2019 / Accepted: 24 September 2019 / Published: 27 September 2019
(This article belongs to the Section Computer Science & Engineering)
OPTICS is a state-of-the-art algorithm for visualizing density-based clustering structures of multi-dimensional datasets. However, OPTICS requires iterative distance computations for all objects and is thus computed in O ( n 2 ) time, making it unsuitable for massive datasets. In this paper, we propose constrained OPTICS (C-OPTICS) to quickly create density-based clustering structures that are identical to those by OPTICS. C-OPTICS uses a bi-directional graph structure, which we refer to as the constraint graph, to reduce unnecessary distance computations of OPTICS. Thus, C-OPTICS achieves a good running time to create density-based clustering structures. Through experimental evaluations with synthetic and real datasets, C-OPTICS significantly improves the running time in comparison to existing algorithms, such as OPTICS, DeLi-Clu, and Speedy OPTICS (SOPTICS), and guarantees the quality of the density-based clustering structures. View Full-Text
Keywords: OPTICS; density-based clustering structure; visualization; constraint graph OPTICS; density-based clustering structure; visualization; constraint graph
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Kim, J.-H.; Choi, J.-H.; Yoo, K.-H.; Loh, W.-K.; Nasridinov, A. A Fast Algorithm for Identifying Density-Based Clustering Structures Using a Constraint Graph. Electronics 2019, 8, 1094.

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