Kelan Ren, Facheng Yan, Honghua Chen, Wen Jiang, Bin Wei, Mingshu Zhang*
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 789-807, 2024, DOI:10.32604/cmc.2024.055624
- 15 October 2024
Abstract The task of cross-target stance detection faces significant challenges due to the lack of additional background information in emerging knowledge domains and the colloquial nature of language patterns. Traditional stance detection methods often struggle with understanding limited context and have insufficient generalization across diverse sentiments and semantic structures. This paper focuses on effectively mining and utilizing sentiment-semantics knowledge for stance knowledge transfer and proposes a sentiment-aware hierarchical attention network (SentiHAN) for cross-target stance detection. SentiHAN introduces an improved hierarchical attention network designed to maximize the use of high-level representations of targets and texts at various… More >
Graphic Abstract