Incremental clustering method and device

Abstract

The embodiment of the invention provides an incremental clustering method and device, which are used for clustering newly added data points each time after primary clustering on the basis of obtaininga primary clustering result according to a density-based hierarchical clustering algorithm. The method comprises the steps that for newly-added data points, the maximum value of the class density ofall classes serves as the neighborhood radius, and the data points in the neighborhoods of the newly-added data points are acquired; and according to the class density of each class to which the datapoint in the neighborhood of the newly added data point belongs, determining the class to which the newly added data point belongs. The device comprises a neighborhood scanning module and an incremental clustering module. According to the incremental clustering method and device provided by the embodiment of the invention, incremental clustering is carried out on the basis of the density-variableclustering result.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of data processing, and in particular, to an incremental clustering method and device. Background technique [0002] Clustering is the process of dividing a collection of physical or abstract objects into multiple classes composed of similar objects, that is, the process of classifying objects into different classes or clusters. Objects in the same class have great similarity, and different classes There is a great deal of dissimilarity between the objects. [0003] There are many types of clustering methods. Although density-based and hierarchy-based clustering algorithms are simple and popular, the existing density-based algorithms have some limitations. [0004] Part of the density-based clustering algorithm, based on the global density, can only provide a relatively single label for the data, and use a single density threshold. For data sets with uneven densities, it cannot produc...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problem existing in the prior art that incremental clustering cannot be performed on the basis of variable density clustering results, embodiments of the present invention provide an incremental clustering method and device

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