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Multi Source Data Association Clustering Analysis Based on Symmetric Encryption Algorithm

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Abstract

Due to the low clustering accuracy of the existing methods, a multi-source data association clustering method based on symmetric encryption algorithm is proposed. The multi-source data acquisition model is established, and the baud interval equalization sampling method is adopted to acquire data. The method of data generalization is applied to classify the collected data attributes optimally, which eliminates the fuzzy data. The symmetric encryption algorithm is used to shorten the range of data query. According to the centrosymmetry of data similarity measurement, multi-source data association clustering is realized. The proposed method can realize different types of data clustering, with high clustering accuracy and strong practical application value.

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Authors and Affiliations

  1. School of Mathematical Sciences, Capital Normal University, Beijing, 100048, China

    Haiqing Wang

  2. School of Economics and Management, Beijing Polytechnic, Beijing, 100176, China

    Haiqing Wang

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  1. Haiqing Wang
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Correspondence to Haiqing Wang.

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Wang, H. Multi Source Data Association Clustering Analysis Based on Symmetric Encryption Algorithm. Mobile Netw Appl 27, 1359–1367 (2022). https://doi.org/10.1007/s11036-022-01922-w

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