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.

中文翻译：

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基于引力搜索的高效三向聚类算法

对象和群集之间存在三种类型的关系，即绝对属于，不确定和不属于绝对。现有的大多数聚类算法代表一个具有单个集合的聚类，它们是双向聚类算法，因为它们仅反映两个关系。相比之下，三向聚类可以通过一对集合直观地反映三种关系类型。但是，三向聚类算法通常需要预先知道阈值，以便获得三种类型的关系。针对这一问题，本文提出了一种基于万有引力思想的高效三向聚类算法。提出的方法可以在聚类过程中自动调整阈值，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常规的双向结果。实验结果表明，所提出的算法不仅可以有效地自动从双向聚类结果中获得三向聚类结果，而且在精度，F-度量，NMI和RI上都有更好的表现。在大多数情况下比较算法。