A vision sensing-enhanced knowledge graph inference method for a healthy operation index in higher education

Yu Nie; Xingpeng Luo; Yanghang Yu; Yu Nie; Xingpeng Luo; Yanghang Yu

doi:10.3934/mbe.2023175

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 2: 3731-3748. doi: 10.3934/mbe.2023175

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Research article Special Issues

A vision sensing-enhanced knowledge graph inference method for a healthy operation index in higher education

Yunnan University of Finance and Economics, Kunming 650221, Yunnan, China

Academic Editor: Man-Fai Leung

Received: 19 October 2022 Revised: 22 November 2022 Accepted: 26 November 2022 Published: 09 December 2022

We adopted the method of knowledge mapping to conduct in-depth visualization to propose the construction method of knowledge mapping-based inference of a healthy operation index in higher education (HOI-HE). For the first part, an improved named entity identification and relationship extraction method is developed, incorporating a vision sensing pre-training algorithm named BERT. For the second part, a multi-decision model-based knowledge graph is used to infer the HOI-HE score by using a multi-classifier ensemble learning approach. The combination of two parts constitutes a vision sensing-enhanced knowledge graph method. The functional modules of knowledge extraction, relational reasoning and triadic quality evaluation are integrated to provide the digital evaluation platform for the HOI-HE value. The vision sensing-enhanced knowledge inference method for the HOI-HE is able to exceed the benefit of pure data-driven methods. The experimental results in some simulated scenes show that the proposed knowledge inference method can work well in the evaluation of a HOI-HE, as well as to discover some latent risk.
- knowledge graph,
- vision sensing,
- healthy operation index,
- data visualization,
- education management
Citation: Yu Nie, Xingpeng Luo, Yanghang Yu. A vision sensing-enhanced knowledge graph inference method for a healthy operation index in higher education[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 3731-3748. doi: 10.3934/mbe.2023175

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Abstract

We adopted the method of knowledge mapping to conduct in-depth visualization to propose the construction method of knowledge mapping-based inference of a healthy operation index in higher education (HOI-HE). For the first part, an improved named entity identification and relationship extraction method is developed, incorporating a vision sensing pre-training algorithm named BERT. For the second part, a multi-decision model-based knowledge graph is used to infer the HOI-HE score by using a multi-classifier ensemble learning approach. The combination of two parts constitutes a vision sensing-enhanced knowledge graph method. The functional modules of knowledge extraction, relational reasoning and triadic quality evaluation are integrated to provide the digital evaluation platform for the HOI-HE value. The vision sensing-enhanced knowledge inference method for the HOI-HE is able to exceed the benefit of pure data-driven methods. The experimental results in some simulated scenes show that the proposed knowledge inference method can work well in the evaluation of a HOI-HE, as well as to discover some latent risk.

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