CLI E-commerce Recommender

Welcome to the CLI E-commerce Recommender, a robust command-line application designed to mimic the functionality of an online e-commerce platform while providing intelligent recommendations to users. This project is a college project developed for the DSC (Data Structures) course.

Project Features

Key Functionalities

1. Sequential Pattern Mining:
   • The recommendation system leverages sequential pattern mining techniques to analyze user purchase patterns and suggest relevant products.
2. Search with Hashmaps:
   • Optimized product asearches using hashmaps
3. E-commerce Features:
   • Product search.
   • Add items to cart and wishlist.
   • Place and manage orders.
4. User Interaction via CLI:
   • Intuitive and user-friendly command-line interface to facilitate seamless navigation and operations.

File Structure

.
├── LICENSE                    
├── README.md                  
├── cart.c                     
├── cli.c                      
├── data.csv                   
├── generated_orders.txt       .
├── list.c                     
├── main.c                     
├── recommender.c              
├── shared.h                   
├── wishlist.c                 

Tech Stack

• Language: C
• Algorithms: Sequential Pattern Mining, Hashmap-based optimizations,weighted probabilities
• File Handling: Persistent data storage using .csv and .txt files.

How to Use

1. Clone the repository:

   git clone https://github.com/swanand11/cli-ecommerce-recommender.git

2. Compile the project using GCC:

   gcc -o program main.c cart.c cli.c list.c recommender.c wishlist.c

3. Run the application:

   ./program

4. Follow the on-screen instructions to navigate the CLI and explore features like product search, adding to cart/wishlist, and viewing recommendations.

Collaborators

This project was collaboratively developed by the following team members:

1. Swanand Gadwe
2. Shrihari Joshi
3. Swaroop Kalli
4. Shubham Khatri

License

This project is licensed under the MIT License.

Future Enhancements

• Integration of more advanced machine learning algorithms for recommendations.
• GUI implementation for a more user-friendly experience.
• Database integration for scalable and dynamic data management.

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We hope you enjoy exploring our CLI E-commerce Recommender project. Happy shopping!