Hierarchical clustering is a common algorithm in data analysis. It unique among many algorithms that it draws dendrograms based on the distance of under certain metric, and group them. widely used all areas astronomical research, covering various scales from asteroids molecular clouds, to galaxies galaxy cluster. This paper systematically reviews history current status development hierarchical ...

Current multiple kernel clustering algorithms compute a partition with the consensus or graph learned from pre-specified ones, while emerging late fusion methods firstly construct partitions each separately, and then obtain one them. However, both of them directly distill information kernels graphs to matrices, where sudden dimension drop would result in loss advantageous details for clustering...

Graph Neural Networks (GNNs) draw their strength from explicitly modeling the topological information of structured data. However, existing GNNs suffer limited capability in capturing hierarchical graph representation which plays an important role classification. In this paper, we innovatively propose capsule network (HGCN) that can jointly learn node embeddings and extract hierarchies. Specifi...

Clustering data has been of great interest to many researchers. Hierarchical clustering methods have been preferred because clusters can be visualized as a dendrogram. One of the problems of hierarchical clustering methods, however, is that the resulting dendrogram is not visually pleasing due to the scaling problem. Hence, a series of iterated logarithmic function is proposed so as to mitigate...

In the hierarchical clustering algorithms, it has become a basic difficult problem to determine the optimal clustering number in the dataset, as a result of the influence of outliers and noise points. Therefore, we propose a method to remove these interferential data in two stages in the hierarchical clustering algorithm, which is based on the traditional noise data removal method. Furthermore,...

The Urban spatial structure is affected by spatial interactions among various activity locations, and land uses in the city over the transportation system. Each city has its unique circulation pattern of passengers and freight due to its unique geographic conditions and the distribution of locations of economic activities. In that sense, it is claimed in this chapter per the authors that urban ...