Research on industry label recognition method based on RoBERTa driven by data

You Wen, Xuan Fan and Pingyan Mo

International Journal of Low-Carbon Technologies, 2025, vol. 20, 626-634

Abstract: This study introduces an enhanced RoBERTa-based model, called Industry Aware RoBERTa (IA-RoBERTa), designed to improve the accuracy and generalization of industry label recognition. IA-RoBERTa innovatively integrates structured industry knowledge through a knowledge graph fusion approach, using multigranularity input representation and industry-aware self-attention mechanisms. Together, these features enhance the model’s ability to efficiently process and understand industry-specific information. In addition, IA-RoBERTa includes a layered industry classifier that expertly handles fine-grained and layered industry categories. Experimental evaluations of industry label recognition datasets show that IA-RoBERTa outperforms existing methods in terms of accuracy, F1 scores, and macro-average performance metrics.

Keywords: industry label recognition; RoBERTa; knowledge graph fusion; pretrained language model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:626-634.

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