Abstract

The widespread adoption of knowledge-based payment systems and numerous online knowledge-based paid items is made possible by the quick development of knowledge information and networking technology. Paid columns were quickly introduced by platforms like Himalaya FM, Zhihu, and Qingting FM, while pay-for- knowledge businesses like Fenda, iGet, and Qianliao quickly went live online. Users rapidly increased, and it was assumed that the knowledge payment progressive trend had been met. This paper aims to examine the emergence of edge computing into the mobile information system into the presence and inevitability of the knowledge payment platform, evaluate the advantages, challenges, and pathways for knowledge payment platform optimization, and try to provide a conceptual suggestion for aiding in its advancement. During data analysis, the independence of the polynomial characteristics was evaluated using Pearson's chi- squared tests. A brand-new meta-heuristic optimizer dubbed Harris Hawks optimization is inspired by how Harris hawks seek food in the wild. According to the experimental results, 98 of the survey's respondents—or 19.1% of all respondents—were under the age of 18; 201 were between the ages of 18 and 29; 142 were between the ages of 30 and 39; and 73 were over 40, or 14.2% of all respondents. The findings indicate a younger age distribution for the sample, with the concentration being highest among those between the ages of 18 and 29, then 30 to 39. The mobile information system edge-based knowledge payment platform has successfully undergone continuous use behavior analysis.

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