International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Al-Powered Sentiment Analysis for Comprehensive Product Review Insights |
|---|---|
| ABSTRACT | AI-Powered Sentiment Analysis for Comprehensive Product Review Insights leverages advanced natural language processing and machine learning techniques to automatically interpret customer opinions expressed in online reviews. This system classifies sentiments, identifies emotions, and extracts key features mentioned by users to generate actionable insights for businesses. By analyzing large volumes of unstructured text data, the model enhances decision-making, improves product quality assessment, and supports customer-centric strategies with high accuracy and efficiency. |
| AUTHOR | PROF VISHWANATH V K, KHUSHAL K M, PAVAN A D, PRATEEKSHA G H, VINOD Assistant Professor, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India UG Student, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312008 |
| pdf/8_Al-Powered Sentiment Analysis for Comprehensive Product Review Insights.pdf | |
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