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Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 7 No 12 (2023): Volume 7, Issue 12, December 2023 | Pages: 132-136
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 19-12-2023
This paper presents a new Chrome extension for predicting star ratings according to the customer's review. Predicto mainly deals with analyzing customer feedback to predict star ratings can provide valuable insights to both consumers and businesses. This research paper presents the development of a Chrome extension designed to predict star ratings based on customer reviews. Leveraging logistic regression as the predictive model, the extension employs natural language processing (NLP) techniques to extract pertinent features from textual feedback. The proposed Chrome extension capitalizes on web scraping capabilities to gather and preprocess customer reviews from diverse online sources. This research contributes to the field of sentiment analysis, customer feedback evaluation, and web scraping by presenting a practical implementation in the form of a user-friendly Chrome extension. The extension's utilization of logistic regression enhances its prediction capabilities and offers a valuable tool for enhancing the online shopping experience and review analysis.
Predicto, Sentiment Analysis, Logistic Regression, Tfidf Vectorizer, Chrome Extension
Sourav Chanda, Abhishek Pandey, Priyanka Mondal, “Predicto - Review Rate Predictor” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 12, pp 132-136, December 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.712018
This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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