An efficient three-way clustering algorithm based on gravitational search
An efficient three-way clustering algorithm based on gravitational search
复制标题
一种基于引力搜索的高效三向聚类算法
DOI：
10.1007/s13042-019-00988-5
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发表时间：
2020
影响因子：
5.6
通讯作者：
Chen Xiaofang
中科院分区：
文献类型：
--
作者：
Yu Hong;Chang Zhihua;Wang Guoyin;Chen Xiaofang
对象和簇之间存在三种关系，即确定属于、不确定和不确定属于。大多数现有的聚类算法都表示具有单个集合的聚类，并且它们是双向聚类算法，因为它们仅反映两种关系。相比之下，三向聚类可以直观地反映一对集合的三种关系。然而，三向聚类算法通常需要提前知道阈值才能获得三类关系。为了解决这个问题，本文提出了一种基于万有引力思想的高效三向聚类算法。该方法可以在聚类过程中自动调整阈值，并获得对象与聚类之间更详细的归属关系。此外，为了保证工作的完整性，我们还提出了一种双向聚类算法来获得传统的双向结果。实验结果表明，该算法不仅能有效地从两路聚类结果中自动获得三路聚类结果，而且在大多数情况下在准确率、F-measure、NMI和RI方面都比对比算法有更好的表现。
There are three types of relationships between an object and a cluster, namely, belong-to definitely, uncertain and not belong-to definitely. Most of the existing clustering algorithms represent a cluster with a single set and they are the two-way clustering algorithms since they just reflect two relationships. By contrast, the three-way clustering can reflect intuitively the three types of relationships with a pair of sets. However, the three-way clustering algorithms usually need to know the thresholds in advance in order to obtain the three types of relationships. To address the problem, we propose an efficient three-way clustering algorithm based on the idea of universal gravitation in this paper. The proposed method can adjust the thresholds automatically in the process of clustering and obtain more detailed ascription relation between objects and clusters. Furthermore, to guarantee the integrity of the work, we also put forward a two-way clustering algorithm to obtain the conventional two-way result. The experimental results show that the proposed algorithm is not only effective to obtain the three-way clustering result from the two-way clustering result automatically, but also it is in a better performance at the accuracy, F-measure, NMI and RI than the compared algorithms in most cases.