Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning

Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning

The evolution of sentiment analysis has increasingly relied on semi-supervised learning (SSL) models, particularly due to their efficiency in utilizing large amounts of unlabeled data. This study employed four Indonesian datasets—Ridife (sentiment classification), Emotion Indonlu (emotion classifica...

Full description

Saved in:
Bibliographic Details
Main Authors: Rochmat Husaini, Nur Heri Cahyana, Wisnalmawati Wisnalmawati, Tri Mardiana, Yuli Fauziah
Format: Article
Language:English
Published: Institut Teknologi Dirgantara Adisutjipto 2025-06-01
Series:Compiler
Subjects:
semi-supervised learning
lstm
sentiment analysis
Online Access:https://ejournals.itda.ac.id/index.php/compiler/article/view/2965
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ejournals.itda.ac.id/index.php/compiler/article/view/2965

Similar Items