Research on Intelligent Text Recognition of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era Based on the BERT Semantic Matching Model

Main Article Content

Y. X. Geng

Abstract

In the digital age, texts related to Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era have experienced rapid growth, creating higher requirements for accurate semantic identification and intelligent text processing. Traditional manual identification methods face bottlenecks such as low efficiency, high subjectivity, and limited coverage, which restrict precise text recognition in ideological dissemination, policy implementation, and technical document management in advanced engineering sectors. This issue is also relevant to standardized documentation in fields such as electromagnetic engineering, antenna systems, and communication technology, where semantic consistency and terminology accuracy are required. This paper aims to improve the semantic accuracy and intelligent efficiency of ideological text recognition by introducing the BERT semantic matching model into the processing of texts on Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era. First, through literature review, the semantic characteristics of ideological texts, including conceptual systematization, multi-level expression, and contextual interdependence, are clarified, together with the limitations of traditional recognition methods. Second, an ideological text corpus is constructed, including 12,000 annotated samples across three text types: core literature, policy documents, and interpretive articles. On this basis, a four-stage recognition process consisting of preprocessing, semantic encoding, similarity calculation, and result optimization is designed to support accurate semantic matching and intelligent text recognition.

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How to Cite
Geng, Y. X. (2026). Research on Intelligent Text Recognition of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era Based on the BERT Semantic Matching Model. Advanced Electromagnetics, 15(3), 1885–1893. https://doi.org/10.7716/aem.v15i3.3236
Section
Research Articles

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