Abstract

In order to effectively ensure the retrieval effect of enterprise data center resources, improve the retrieval accuracy of enterprise data center resources, and shorten the retrieval time of enterprise data center resources, a retrieval technology of enterprise data center resources based on density peak clustering algorithm is proposed. Analytical clustering algorithms, density clustering algorithms, and density peak clustering algorithms are all types of clustering algorithms. To reduce the dimensionality of enterprise data center resources, the kernel principal component analysis method is used. The structure of the enterprise data center resource set is reorganized and the feature quantity of the enterprise data center resource distribution is extracted using feature space reorganization technology. On this basis, the density peak clustering is carried out on the data center resource set of enterprise, and the semantic association distribution model of data center resource retrieval in enterprise is constructed. Through the semantic registration and weighted vector combination control method, the retrieval of enterprise data center resources is realized. The experimental results show that the proposed algorithm has a good effect on the retrieval of enterprise data center resources, which can effectively improve the resource retrieval accuracy and shorten the resource retrieval time.

Keywords

Cite this article

@article{cai-6223,
  author  = {Jiaming Jiang and Guoheng Ruan and Zhenggan Dai},
  title   = {Retrieval Technology of Enterprise Data Center Resources Based on Density Peak Clustering Algorithm},
  journal = {Computing and Informatics},
  volume  = {42},
  number  = {4},
  pages   = {923--942},
  year    = {2023},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2023_4_923}
}
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