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| Interdisciplinary Measurement Research Based on Reference Literature and Text Content Subject Classification |
| Lyu Qi1, Shangguan Yanhong2, Li Rui1 |
1.School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou 450046
2.School of Management, Zhengzhou Shengda University, Zhengzhou 451191 |
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Abstract Currently, the world is facing several scientific challenges that require collaborative efforts from multiple fields and disciplines to solve them in various ways. Therefore, grasping the development trend of interdisciplinary integration and exploring the degree of interdisciplinary research in different disciplines is an important research direction. This paper combines reference and text content information to construct a citation embedding SCIBERT attention model, which classifies journal literature by discipline and conducts interdisciplinary measurement research based on the results of discipline classification. Simultaneously, the feasibility and effectiveness of the method proposed in this study are verified by comparing it with interdisciplinary measures of single input references and text content. Research has found that integrating text content and reference information can effectively achieve disciplinary classification of journal literature, which is better than disciplinary classification with a single input of information. A disciplinary classification based on references and text content can effectively conduct interdisciplinary measurement. The granularity of the disciplinary classification system will affect the disciplinary classification effectiveness of journal literature.
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Received: 07 September 2023
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