📞 +91-7667918914 | ✉️ ijarcce@gmail.com
IJARCCE Logo
International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 14, ISSUE 3, MARCH 2025

Sentiment-Aware and Explainable AI-Based Cross-Domain Recommendation System

Monisha Linkesh, Minakshi Ghorpade, Jisha Tinsu

DOI: 10.17148/IJARCCE.2025.14385

Abstract: Cross-Domain Recommendation Systems (CDRS) enhance traditional recommendation models by transferring knowledge across different domains, thereby improving the personalization of suggested content. The integration of Explainable AI (XAI) ensures transparency in recommendation systems, addressing concerns regarding trust and interpretability. Additionally, sentiment analysis is crucial in refining recommendations by capturing the emotions embedded in user reviews and feedback. This paper explores the concept of a sentiment-aware and explainable AI-based cross-domain recommendation system by discussing key methodologies, challenges, and potential advancements in the field. The research highlights how a hybrid recommendation model can optimize user satisfaction by balancing accuracy, interpretability, and personalized content delivery.

Keywords: Cross-Domain Recommendation, Explainable AI, Sentiment Analysis, Hybrid Recommendation Model, User Trust.

How to Cite:

[1] Monisha Linkesh, Minakshi Ghorpade, Jisha Tinsu, “Sentiment-Aware and Explainable AI-Based Cross-Domain Recommendation System,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14385