Jiawen Wang

Mitigating unreliable syntactic dependencies in aspect-based sentiment analysis via sentiment-aware graph anomaly detection and mix convolution.

A sentiment-aware graph anomaly detection framework that integrates graph anomaly detection with a sentiment consistency evaluation mechanism to eliminate misleading dependencies and preserve key sentiment information from the original graph and can be seamlessly incorporated into other graph-based ABSA models to enhance performance and robustness.