Earticle

초록

영어

In this paper, a model combined with explanatory artificial intelligence (xAI) models was presented to secure the reliability of machine learning-based sentiment analysis and prediction. The applicability of the proposed model was tested and described using the IMDB dataset. This approach has an advantage in that it can explain how the data affects the prediction results of the model from various perspectives. In various applications of sentiment analysis such as recommendation system, emotion analysis through facial expression recognition, and opinion analysis, it is possible to gain trust from users of the system by presenting more specific and evidence-based analysis results to users.

목차

Abstract
1. Introduction
2. Theory
2.1 XAI (Explainable AI)
3. XAI-based sentiment analysis system model
3.1 Experimental dataset
3.2 Model Training
4. Interpretation of explanation based on the proposed model
4.1 LIME Explanations of News group dataset
4.2 SHAP based Explanations of IMDB dataset
5. Conclusions
Acknowledgement
References

키워드

저자

• Mi-Hwa Song [ Assistant Professor, School of Smart IT, Semyung University, Jecheon, Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380