ملف الباحث

Saike He

ورقة واحدة في مجموعة PaperMetrix

المنشورات

أوراق هذا المؤلف

  1. Interpretability in Sentiment Analysis: A Self-Supervised Approach to Sentiment Cue Extraction

    2024 · Applied Sciences

    In this paper, we present a novel self-supervised framework for Sentiment Cue Extraction (SCE) aimed at enhancing the interpretability of text sentiment analysis models. Our approach leverages self-supervised learning to identify and highlight key textual …