Title: Data analysis method of university bidding and purchasing based on improved Apriori algorithm

Authors: Tianyu Feng

Addresses: Department of Assets and Logistics Management, Office of Tender Management, Suzhou University of Science and Technology, Suzhou, 215000, China

Abstract: With the increasing scale of university bidding projects and funds year by year and the development trend of "Internet + bidding and procurement", the establishment of high-quality data analysis methods has become the focus of building an Internet-based University bidding and procurement management system. In view of the shortcomings of traditional data analysis methods, based on the analysis of the construction strategy of university bidding and procurement, this study designs a data analysis method of University bidding and procurement based on improved Apriori algorithm. According to the experimental results, the method has high analysis timeliness, accuracy and stability, indicating that the method effectively achieves the design expectation.

Keywords: higher education; bidding procurement; data analysis; feature recognition; improved Apriori algorithm; the characteristics of clustering.

DOI: 10.1504/IJISD.2025.145965

International Journal of Innovation and Sustainable Development, 2025 Vol.19 No.3, pp.327 - 343

Received: 30 May 2022
Accepted: 02 Feb 2023
Published online: 01 May 2025 *

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