Title: An evaluation method of innovation and entrepreneurship ability of college students based on implicit knowledge mining

Authors: Shuyan Xue

Addresses: Department of Recruitment and Employment, Henan Polytechnic Institute, NanYang, 473000, China

Abstract: To address the issues of low accuracy, poor discrimination, and limited user friendliness in traditional methods of assessing entrepreneurial ability, this paper introduces a new assessment method for college students' innovation and entrepreneurship ability, which is grounded in implicit knowledge mining. Firstly, collect data on innovation and entrepreneurship capabilities and construct an evaluation index system. Then, analyse the correlation between the data using association rules, mine the implicit knowledge features of the data utilising implicit knowledge mining techniques, and categorise the data accordingly. Finally, calculate the weight of the evaluation indicators using the comparison method and entropy method, and construct a competency evaluation function to obtain the competency evaluation results. The experiment demonstrates that the accuracy of this method exceeds 95%, the discrimination rate surpasses 0.90, and the user-friendliness reaches 97.75%, thus validating the efficacy of the innovation and entrepreneurship ability evaluation method proposed in this paper.

Keywords: association rule analysis; innovation and entrepreneurship ability; ability assessment; implicit knowledge mining; entropy method.

DOI: 10.1504/IJBIDM.2025.143936

International Journal of Business Intelligence and Data Mining, 2025 Vol.26 No.1/2, pp.174 - 189

Received: 18 Dec 2023
Accepted: 31 May 2024
Published online: 14 Jan 2025 *

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