Abstract
The comparison of two objects is a topic that exists widely in different research areas. In this study, the network distance is combined with the k-nearest neighbour network sequence to construct the topological structural distance (TSD). This indicator is used to quantitatively describe the difference between two sets of points in any metric structure. Several datasets were tested to demonstrate the effectiveness of this indicator. Calculations show that TSD can compare the intrinsic structure of low-dimensional and high-dimensional datasets and is not limited by dimension. In addition, TSD can also be used to characterize sets of points in discrete space, such as comparing the structure of different networks. The examples in this study show that TSD is a universal method for analyzing the intrinsic structure of data.
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