Vectorized Discourse Polarity Prediction Model Using NLP |
Author(s): |
| Ms.D.Bhavana , Bharath Institute of Higher Eduaction and Research; Kumbam Sai Kiran, Bharath Institute of Higher Eduaction and Research; Kommuri Nitheesh, Bharath Institute of Higher Eduaction and Research; Kurva Yugendhar , Bharath Institute of Higher Eduaction and Research; Kuncha Venkata Karthik, Bharath Institute of Higher Eduaction and Research |
Keywords: |
| NLP, Sentiment Analysis, E-commerce, Java, SQL, Customer Reviews, Product Ranking, Vectorization, and Polarity Prediction |
Abstract |
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Vectorized Discourse Polarity Prediction on Model that integrates Natural Language Processing (NLP), Java, and SQL database ranking mechanisms. The framework is designed to address the challenges of manual feedback analysis in e- commerce, when customers submit reviews, the system analyzes the text using NLP techniques like preprocessing and vectorization on to classify the feedback as positive, negative, or neutral. Based on this sentiment, a weighted scoring algorithm automatically updates product rankings in an SQL database. The system provides an intelligent and scalable solution that enhances user experience and supports decision-making by giving higher visibility to products with positive feedback and ranking poorly rated products lower or filtering them out. This approach ensures the maintenance of product quality in both online and offline shopping environments. |
Other Details |
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Paper ID: IJSRDV13I90075 Published in: Volume : 13, Issue : 9 Publication Date: 01/12/2025 Page(s): 76-79 |
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