Data-field-based automatic clustering method

An automatic clustering and data field technology, applied in the field of cluster analysis, to achieve good robustness, improve computing speed, and avoid noise processing

Active Publication Date: 2012-05-02
WUHAN UNIV
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Problems solved by technology

[0004] In view of the above technical problems, the purpose of the present invention is to propose a fast and efficient automatic clustering method based on the data field to solve the speed and efficiency problems when clustering a large amount of data

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Embodiment Construction

[0026] Inspired by the field theory in physics, Wang Shuliang and others put forward the idea of ​​data field. Data radiates its data energy from the sample space to the entire parent space through data radiation, and the space that receives data energy and is covered by data radiation is called data field. The data field can be regarded as a space full of data energy, the data transmits energy to another data in the field through its own data field. The data points in the data field radiate energy to each other, and these energies superimpose each other to form the potential of the data field. According to different data objects, the field strength function of the data field can be defined in various forms. In the present invention, the nuclear radiation derived field is used, and the corresponding potential function is as formula (1).

[0027] Formula (1)

[0028] Among them, x, y are two data points, σ ​​is the influence factor of the data field, ||x-y|| 2 is the Eucli...

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Abstract

The invention relates to a data-field-based automatic clustering method. In the method, each space data is taken as a data point with mass, and the space data influence each other to form a data field, wherein total influence of all data points at a specific position represents the potential value of the data field. Points where the first-order partial derivative value of the potential value of the data field is zero are in an area where data superposition is most intensive, namely data cluster centers. The data-field-based automatic clustering method finds out the data cluster centers by searching the first-order derivative of the potential value of the data field, and searches the two sides according to the cluster centers and determines the edges of the clusters, thus finally marking complete clusters. Compared with the transitional clustering method, the data-field-based automatic clustering method has fast processing speed, is not influenced by noise, and is effective for clusters in any shapes, can be applied to the fields of image processing, community discovering, abnormal detection, market research and the like, thus improving the accuracy of the processing result.

Description

technical field [0001] The invention relates to the technical field of cluster analysis, in particular to an automatic clustering method based on a data field. Background technique [0002] As an important research content in the field of spatial data mining, clustering method can divide a collection of physical or abstract objects into similar object classes, so as to help people discover the potential knowledge hidden behind the data. very important meaning. At present, clustering methods have been widely used in image processing, anomaly detection, Web hotspot discovery, community discovery, credit card fraud detection, business data analysis and so on. [0003] Cluster analysis divides a large data set into groups according to the similarity of the data, and each group after the division is a cluster. A cluster is a collection of data objects that are similar to objects in the same cluster and different from objects in other clusters. Depending on the characteristics ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 王树良陈亚森
Owner WUHAN UNIV
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