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A personalized e-commerce recommendation system powered by Neo4j, leveraging graph-based collaborative filtering, Jaccard similarity, and content-based filtering to enhance user engagement and sales.

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E-commerce Recommendation System with Neo4j

This project implements a personalized product recommendation system using Neo4j, a graph database, to enhance user engagement and sales in e-commerce platforms.

Features

  • Collaborative Filtering
  • Jaccard Index for Similarity
  • Content-Based Filtering
  • Most Popular Products Highlight

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Check the full blog article here

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A personalized e-commerce recommendation system powered by Neo4j, leveraging graph-based collaborative filtering, Jaccard similarity, and content-based filtering to enhance user engagement and sales.

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