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Recommendation System for Appliances, along with Topic Modelling and Sentiment Analysis

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AppliRec: User-Based Collaborative Filtering for Appliances

In the ever-evolving landscape of e-commerce, customer reviews are pivotal in guiding purchasing decisions. Home appliances constitute a significant domain among the multitude of products available on platforms like Amazon. It is anticipated that the household appliances eCommerce market in the United States will reach US$48,404.9 million by the end of 2023, making up 84.3% of the country's electrical appliance eCommerce industry. Due to the fierce competition in the e-commerce market, it is important to harness new tools and technologies to be a market leader in a category. Analyzing and making use of the wealth of user-generated reviews in the Appliances category on Amazon can provide valuable insights into product preference and user sentiments.

The "AppliRec" project is designed to explore and leverage this vast repository of product reviews in the Appliances domain on Amazon. This project uses a user-based collaborative filtering recommendation system. E-commerce platforms witness significant demand for appliances like Cooktops, Ranges, Compactors, Trash Compactors, Dishwashers, Ice Makers, and Freezers, where the provided information plays a crucial role in purchasing decisions. Implementing a user-based recommendation system in such categories holds immense value. By showcasing products highly rated by users similar to an individual, this system becomes a pivotal tool. Its application across diverse sections of an e-commerce platform can enhance user engagement, prolong user sessions, and potentially increase the likelihood of successful checkouts.

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Project Report: Click here to view the Project Report

Project Pitchdeck: Click here to view the Project Pitchdeck

Contributors

Roshni Balasubramanian & Dhruv Arora
In fulfilment of Modern Analytics (DECISION546Q), Duke University, Fuqua School of Business

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Recommendation System for Appliances, along with Topic Modelling and Sentiment Analysis

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