CHOLD: Offensive Language Detection Method for Chinese Texts

Houyue Wu

doi:10.1007/978-981-95-5294-8_17

2026-01-01

PRE

Houyue Wu

Xianwei Li *

S. S. Zhang

DOI：10.1007/978-981-95-5294-8_17

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摘要

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针对净化网络空间和确保预训练语言模型高效有序运行，恶意语言检测至关重要。传统恶意语言检测方法依赖单一匹配机制，常忽略语义偏差对检测结果的影响，导致准确率低，对网络安全构成威胁。为解决此问题，本文提出一种高精度中文恶意语言检测方法CHOLD。CHOLD整合汉字字形、发音和语义等多维度语言特征，首先构建多样化的恶意语言关键词列表以进行语义匹配目标句，随后将匹配词加入关键词列表形成候选集。对候选集内句子进行降维后，融合字形、发音和语义的高维特征，并采用语义约束方法减小语义偏差对结果的影响。在多个公开数据集上的实验表明，CHOLD在识别准确率方面优于现有检测模型。

Keyword:

Offensive Language

Information Detection

Semantic Constraint

Text Semantic Deviation

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COMPUTER APPLICATIONS, CCF NCCA 2025

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Bengbu University

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589

论文数: 343

被引数: 181

anhui university of science & technology

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1.1K

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