Titlebook: Web and Big Data; 6th International Jo Bohan Li,Lin Yue,Toshiyuki Amagasa Conference proceedings 2023 The Editor(s) (if applicable) and The

終點(diǎn)

Conclave

Strength

混雜人

不遵守

碎石

胡言亂語

不近人情

ToSA: A Top-Down Tree Structure Awareness Model for?Hierarchical Text Classificationroduce a priori hierarchical information in the decoding process. We block the information flow in one direction to ensure the graph embedding method is more suitable for the HTC task, then get the enhanced tree structure representation. Experiment results show that our model can achieve the best re

教義

Clause Fusion-Based Emotion Embedding Model for Emotion-Cause Pair Extractionevel feature in the sliding-window is fused to fused emotion features. The fused emotion features, cause word-level, and emotion word-level feature representation are embedded to get emotion embedding. Third, the emotion embedding is processed to the cause clause feature representation by a bidirect

UTTER

Clause Fusion-Based Emotion Embedding Model for Emotion-Cause Pair Extractionevel feature in the sliding-window is fused to fused emotion features. The fused emotion features, cause word-level, and emotion word-level feature representation are embedded to get emotion embedding. Third, the emotion embedding is processed to the cause clause feature representation by a bidirect