{"id":27156654,"url":"https://github.com/tejas-130704/tejkart","last_synced_at":"2026-05-07T18:36:00.390Z","repository":{"id":286827862,"uuid":"962681954","full_name":"tejas-130704/Tejkart","owner":"tejas-130704","description":"A dynamic e-commerce platform that recommends products based on what you view, add to cart, and review. 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It integrates **Computer Vision**, **Natural Language Processing (NLP)**, and **User Behavior Analysis** to deliver personalized product recommendations.\n\n---\n\n## 🚀 Features\n\n### 🧠 AI-Powered Recommendation System\n- **NLP-Based Similar Product Recommender**\n  - Uses product descriptions and metadata to find semantically similar items.\n  \n- **Computer Vision-Based Similarity**\n  - Uses CNN-based image feature extraction to recommend visually similar products.\n\n- **Sentiment Analysis on Product Reviews**\n  - Automatically analyzes user reviews (positive/negative) using an RNN-based model trained on Amazon review data.\n  - Sentiment scores contribute to personalized recommendation logic.\n\n- **User Interest Algorithm**\n  - Tracks user behavior like:\n    - Adding products to cart\n    - Searching for specific items\n    - Reviewing products\n  - Assigns **Interest Points** to product categories based on actions and sentiment.\n  - Dynamically recommends products from the most relevant categories.\n\n### 🛒 E-Commerce Platform Essentials\n- User registration \u0026 login with JWT Authentication\n- Product browsing, search, and filtering\n- Secure cart and checkout flow\n- Product reviews and rating system\n\n---\n\n## 🛠️ Tech Stack\n\n| Layer | Technology |\n|-------|------------|\n| **Frontend** | React.js, Tailwind CSS |\n| **Backend** | Django, Django REST Framework |\n| **Authentication** | JSON Web Tokens (JWT) |\n| **ML/NLP** | Python, Scikit-learn, NLTK, RNN (for sentiment analysis), TF-IDF |\n| **Computer Vision** | CNN (Convolutional Neural Networks), OpenCV |\n| **Database** | PostgreSQL / SQLite |\n\n---\n\n## 🧠 Recommendation Workflow\n\n```mermaid\ngraph TD\nA[User Registers and Logs In] --\u003e B[Views Product]\nB --\u003e C[NLP and CV Based Recommendations]\nB --\u003e D[Writes Review or Adds to Cart]\nD --\u003e E[Sentiment Analysis via RNN]\nD --\u003e F[Category Interest Tracking]\nE --\u003e G[Update Interest Points - Positive or Negative]\nF --\u003e G\nG --\u003e H[Personalized Category-Based Recommendations]\n\n```\n\n---\n\n## ⚠️ Note About Repository Size \u0026 Missing Files\n\n\u003e Due to GitHub's storage limitations, some **large files including trained ML models** (`.h5`, `.pkl`, etc.) have **not been pushed to the repository**.  \n\u003e The entire project exceeded GitHub's file size limits, so you may also notice **some major components (e.g., datasets, pre-trained models, or media folders) are missing**.\n\nIf you’re interested in running or testing the full application, feel free to contact me for access to the full project files and models.\n\n---\n\n## 💡 Future Enhancements\n\n- Collaborative filtering with hybrid recommendation\n- Recurrent user profiling with long-term interest tracking\n- Deployment using Docker + CI/CD\n- Admin dashboard with AI insights (product trends, user interest heatmaps)\n\n---\n\n## 📬 Contact\n\nCreated with ❤️ by **Tejas Narayan Jadhav**  \n📧 Email: [tejasjadhav130704@example.com]  \n🔗 LinkedIn: [https://www.linkedin.com/in/tejas-jadhav-385613256/](https://linkedin.com)\n\n---\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftejas-130704%2Ftejkart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftejas-130704%2Ftejkart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftejas-130704%2Ftejkart/lists"}