Product Recommendation Based On Sentiment Analysis Of Genuine Reviews

Registration ID: IJNRD_194921

Published ID: IJNRD2305307

DOI: Click Here to Get

Shivananda V Seeri , Ajnya V Naik , Bhagyashree Ramachandra , Mridul Rajeev , Prajna G

Sentiment Analysis, Product Recommendation, Preprocessing, Machine Learning, Logistic Regression.

In the era of online shopping, product reviews have gained immense significance as a determining factor in the consumer's decision-making process. Customers heavily rely on reviews to assess the quality and dependability of products prior to making a purchase. This study proposes a recommendation system for Amazon electronics products that incorporates ML algorithms, including XGBoost, logistic regression, CatBoost. The dataset used here in this project consists of Amazon electronics reviews obtained from Jmcauley's website, which includes reviews, ratings, product title, product id and reviewer details. The system applies these algorithms to classify reviews as negative or positive and recommends products depending on sentiment score of positive reviews. The algorithms underwent training using a preprocessed dataset, and their performance was assessed by evaluating their accuracy using a separate testing dataset. Findings revealed that XGBoost yielded the highest accuracy, achieving 86.42%, followed by CatBoost which yielded the accuracy of 85.3% and logistic regression gave an accuracy of 84.8%.

Published Paper   E-Certificate

Shivananda V Seeri, Ajnya V Naik, Bhagyashree Ramachandra, Mridul Rajeev, & Prajna G (May-2023). Product Recommendation Based On Sentiment Analysis Of Genuine Reviews . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), d49-d53. https://ijnrd.org/papers/IJNRD2305307.pdf

Volume 8 Issue 5, May-2023

Pages : d49-d53

Paper Reg. ID: IJNRD_194921

Published Paper Id: IJNRD2305307

Downloads: 000121977

Research Area: Engineering

Country: Udupi, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305307.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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