计算机工程与应用2025，Vol.61Issue(6)：220-228,9.DOI:10.3778/j.issn.1002-8331.2311-0035
融合位置信息和交互注意力的方面级情感分析
Aspect-Level Sentiment Analysis Incorporating Location Information and Interaction Attention
摘要
Abstract
A large number of commentary texts appear on social media and e-commerce platforms,and attention-based aspect-level sentiment analysis methods have been widely used to analyze these texts.When the existing methods achieve the interactive attention between aspect words and context,there is no use of the relative positional relationship between context and aspect words,and only focus on the influence of aspect words on the context,resulting in insufficient semantic interaction,and the aspect words as a whole.An aspect-level sentiment analysis model with interactive attention incorpo-rating relative position information is proposed.Firstly,the bidirectional long short-term memory network is used to learn the semantic features of the aspect words and context that fuses the location information,and then the learnable parameter matrix is integrated to conduct interactive learning of the semantic features of context and aspect words,and interactive attention is used to calculate the impact of aspect words on context and the impact of context on aspect words at word granularity.Finally,sentiment classification is carried out.Several experiments are conducted on the SemEval 2014 Task4 and Twitter benchmark datasets.The experimental results show that the proposed model achieves better performance than the comparison methods.关键词
方面级情感分析/位置信息/交互注意力/深度学习Key words
aspect-based sentiment analysis/position information/interactive attention/deep learning分类
信息技术与安全科学引用本文复制引用
李佳静,李盛,戴媛媛,孟涛,罗小清,闫宏飞..融合位置信息和交互注意力的方面级情感分析[J].计算机工程与应用,2025,61(6):220-228,9.基金项目
国家自然科学基金(51674762). （51674762）
