Abstract
In the multi-method and multi-model collaborative matrix model clustering calculation analysis, the talent evaluation sample data itself is used as a dictionary to re-represent each sample data, and the sample-based collaborative data reconstruction is carried out, and the talent evaluation reconstruction coefficient matrix is sparse, Low rank and smooth constraints greatly improve the reliability and validity of enterprise talent evaluation samples[1]. The main purpose of this paper is to design and construct a multi-model and multi-view collaborative similarity matrix for enterprise talent assessment, to mine the relationship between talent assessment samples, and to achieve clustering and collaboration of assessment samples.
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