Multi-view information bottleneck clustering algorithm integrating double relation
An information bottleneck and clustering algorithm technology, applied in computing, computer parts, instruments, etc., can solve problems such as clustering performance decline, achieve good clustering results, and improve clustering performance.
Pending Publication Date: 2022-01-07
ZHENGZHOU UNIV
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[0004] The embodiment of the present invention provides a multi-view information bottleneck clustering algorithm with comprehensive double linkage, which mainly solves the problem that the existing multi-view clustering algorithm fails to fully consider the characteristics of multi-view data and the relationship between data clusters, which leads to the decline of clustering performance
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[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these examples are only used to illustrate the present invention and not to limit the scope of the present invention. After reading the present invention, modifications to various equivalent forms of the present invention by those skilled in the art fall within the scope defined by the appended claims of the present application.
[0028] The present invention is a kind of multi-view information bottleneck clustering algorithm of comprehensive double relation, and its overall frame is as follows figure 1 As shown, the specific steps are as follows:
[0029] S1. Acquire multi-view text, image or video data x={x 1 , x 2 ,...,x n}, n represents the number of input data; among them, various m...
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The invention discloses a multi-view information bottleneck clustering algorithm integrating double relations. The multi-view information bottleneck clustering algorithm comprises the following steps of: S1, acquiring multi-view text, image or video data; S2, preprocessing the multi-view data; S3, discovering personalized feature information of each view angle by adopting an information bottleneck method; S4, finding out generalization feature information among visual angles by learning a multi-visual-angle shared feature subspace; S5, integrating the personalized feature information of each view angle and the generalization feature information of the view angles to obtain a local clustering result of each view angle; and S6, mining close relations among the local clustering results to obtain a final global data clustering result. The multi-view information bottleneck clustering algorithm aims at comprehensively mining and utilizing double relations such as features and data clusters of multi-view data, the problem that information of the features and the data clusters is not fully considered in a current multi-view algorithm is solved, and the clustering performance is greatly improved.
Description
technical field [0001] The invention belongs to the field of clustering analysis in pattern recognition, in particular to a multi-view information bottleneck clustering algorithm with comprehensive double links. Background technique [0002] Multi-view clustering aims to mine and utilize complementary information between multiple view data to obtain effective clustering results with consistent views. In recent years, a large number of multi-view clustering algorithms have been proposed and successfully applied to many practical fields, such as transportation, education, medical care, finance, etc. However, a large number of current multi-view clustering algorithms only consider the features between views or the association relationship of data clusters, and fail to mine and make full use of the advantages of the two for data division. This has brought great challenges to the practical applicability of current algorithms, and a multi-view algorithm that can take into account...
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IPC IPC(8): G06K9/00G06K9/62
CPCG06F18/23
Inventor 叶阳东胡世哲
Owner ZHENGZHOU UNIV