Title: Group computing task assignment and association analysis based on big data technology

Authors: Chen Ting

Addresses: College of Electronic Information Engineering, Xi'an Siyuan University, Xi'an, Shaanxi, China

Abstract: The explosion of data scale makes data processing encounter many difficulties and challenges. The purpose of this paper is to discuss the group computing task assignment and correlation analysis of big data technology. This paper designs and proposes an algorithm for task assignment in big data sets, which is based on the user's exact perception of a topic and aims to improve the accuracy of calculation. This algorithm is first able to effectively combine the topic accurate perception and extraction model with adaptive fuzzy clustering, and then it can be done by building a model that focuses on specific target groups and users, and calculating the degree between them. The experimental results of this paper show that the accuracy of the music dataset is relatively low, averaging 50%; for the compilation of thematic data sets, the accuracy rate is high, averaging 70%; the final task assignment accuracy reaches 79.9%.

Keywords: big data technology; group computing; task assignment; association analysis; self-processing algorithm.

DOI: 10.1504/IJGUC.2024.140110

International Journal of Grid and Utility Computing, 2024 Vol.15 No.3/4, pp.263 - 272

Received: 10 Feb 2023
Accepted: 13 Apr 2023
Published online: 24 Jul 2024 *

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