计算机工程与应用2024，Vol.60Issue(5)：112-121,10.DOI:10.3778/j.issn.1002-8331.2210-0231
面向方面级情感分析的多视图表示模型
Multi-View Representation Model for Aspect-Level Sentiment Analysis
摘要
Abstract
The fine-grained sentiment analysis of user comments for specific aspects is a popular research topic in the field of natural language processing.For the flexibility of comment statements in content expression and syntactic struc-ture,the integrated use of lexical,syntactic and semantic knowledge to enhance the feature representation of comment statements is a major research idea at present.Based on this,a graph convolutional network model for multi-view fusion representation is proposed in this paper.First,the model learns to obtain context-based enhanced representations of com-ment statements through self-attention and aspect-specific attention.Second,two different representations of comment utterances based on syntax and semantics are obtained through graph convolution operations using syntactic dependency information and word co-occurrence information,respectively.Finally,a hierarchical fusion approach is designed based on obtaining three different view representations to achieve information sharing and complementarity among different view representations by combining and convolving the three representations.Experimental results on five publicly avail-able datasets show that the model achieves better performance than existing models.关键词
方面级情感分析/图卷积网络/注意力机制/多视图表示Key words
aspect-level sentiment analysis/graph convolution network/attention mechanism/multiview representation分类
信息技术与安全科学引用本文复制引用
徐学锋,韩虎..面向方面级情感分析的多视图表示模型[J].计算机工程与应用,2024,60(5):112-121,10.基金项目
国家自然科学基金(62166024). （62166024）
