Title: Study on microblog public opinion data mining algorithm based on multi-visual clustering model

Authors: Lin-lin Li; Wei-zhen Hou; Jing Liu

Addresses: School of Information Resources Management, Renmin University of China, Beijing, 100872, China; Information Institute, Transport Planning and Research Institute Ministry of Transport, Beijing, 100028, China ' School of Information Resources Management, Renmin University of China, Beijing, 100872 China ' School of Information Resources Management, Renmin University of China, Beijing, 100872 China

Abstract: Because of the random distribution of microblog public opinion data, it is difficult to mine, this paper proposes a microblog public opinion data mining algorithm based on multi vision clustering model. It constructs the phase space distribution structure model of microblog public opinion data, the fuzzy association rule distribution set of microblog public opinion data, analyses the high-order statistical characteristics of microblog public opinion data, and advances the data of fuzzy clustering center according to the different statistical characteristics Row partition block scheduling. The binary structure of microblog public opinion data is reconstructed in the virtual database, and multi angle fuzzy clustering is carried out according to the reconstruction results to realise the optimised mining of microblog public opinion data. The simulation results show that the mining time of this method is up to 4.13 MS and the mining accuracy is up to 100%.

Keywords: multi-visual clustering; microblog; public opinion data; mining algorithm; simulation.

DOI: 10.1504/IJAACS.2020.109810

International Journal of Autonomous and Adaptive Communications Systems, 2020 Vol.13 No.2, pp.151 - 165

Received: 09 Sep 2019
Accepted: 04 Dec 2019
Published online: 24 Sep 2020 *

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