计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 240400193-7.doi: 10.11896/jsjkx.240400193
黄志勇, 李弼程, 魏巍
HUANG Zhiyong, LI Bicheng, WEI Wei
摘要： 随着网络上越来越多的人发表自己的观点,带有情绪的贴文也逐渐增多,负面情绪的累积可能导致舆论失控,准确地识别贴文的情感极性能有效分析舆论现状。目前方面级的情感分析尚未有效融合语法信息以及语义信息,无法同时考虑语法结构的互补性和语义相关性。为此,提出了一个融合语法和语义的方面级情感分析模型(Aspect-level Sentiment AnalysisMo-dels Based on Syntax and Semantics,SS-GCN),包括语法分析模块、语义分析模块以及融合模块。首先将文本作为预训练BERT模型的输入,通过语法分析模块获得语法关联关系的特征表示,同时经由邻域增强机制的语义分析模块捕获语义的相关性的特征表示。最后把二者输入到融合模块,在仿射变换的作用下对语法信息和语义信息进行有效的交互和融合,实现方面级情感分析。
中图分类号:
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