Harnessing holistic discourse features and triadic interaction for sentiment quadruple extraction in dialogues

• Main Authors: LI, Bobo, FEI, Hao, LIAO, Lizi, et al
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Feature models; Heterogeneous graph; Performance; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9640; https://ink.library.smu.edu.sg/context/sis_research/article/10640/viewcontent/Harnessing_Holistic_Discourse_Features_and_Triadic_Interaction_for_Sentiment_Quadruple_Extraction_in_Dialogues.pdf
• Institution: Singapore Management University

Dialogue Aspect-based Sentiment Quadruple (DiaASQ) is a newly-emergent task aiming to extract the sentiment quadruple (i.e., targets, aspects, opinions, and sentiments) from conversations. While showing promising performance, the prior DiaASQ approach unfortunately falls prey to the key crux of DiaA...