Computer Science, Human-Computer Interaction, Information Systems, Software
3
Scopus Publications
Scopus Publications
SentimentLP: unveiling advanced sentiment analysis through Leptotila optimization-based gradient boosting machines Anitha Merlin Durairaj John Louis, Vimal Kumar Dhanasekaran Bulletin of Electrical Engineering and Informatics, 2025 Sentiment analysis is pivotal in extracting insights from textual data, enabling organizations to understand customer opinions, market trends, and brand perception. This study introduces a novel approach, SentimentLP, which integrates Leptotila optimization (LPO) with gradient boosting machines (GBM) for sentiment analysis tasks. The proposed framework leverages LPO’s dynamic optimization capabilities to enhance GBM models’ performance in sentiment classification. Through iterative refinement and adaptive learning, SentimentLP optimizes feature extraction, model training, and ensemble learning processes, improving sentiment analysis accuracy and efficiency. Results from various evaluation metrics, including precision, recall, classification accuracy, and F-measure, demonstrate the effectiveness of SentimentLP in accurately capturing sentiment expressions in text data. Additionally, the fusion of LPO with GBM ensures scalability, adaptability, and interpretability of sentiment analysis models, making SentimentLP a valuable tool for extracting actionable insights from textual data across diverse domains and applications.
EXPLORING ARO-LOGISENT: DELVING INTO DATA COLLECTION FOR ADVANCED SENTIMENT ANALYSIS WITH AMAMI RABBIT OPTIMIZATION-BASED LOGISTIC REGRESSION Journal of Theoretical and Applied Information Technology, 2024
PERCEPTIVE GENETIC ALGORITHM-BASED WOLF INSPIRED CLASSIFIER FOR BIG SENTIMENT DATA ANALYSIS Journal of Theoretical and Applied Information Technology, 2022
