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E-commerce Product Recommendation System

Overview

This project focuses on enhancing the online shopping experience through personalized product recommendations on an e-commerce platform. Developed by Group 14, the system aims at boosting sales, user engagement, and maintaining an efficient inventory system.

Project Structure

The repository is organized as follows:

  • SQL Scripts: Contains all the SQL functions, triggers, and stored procedures essential for data manipulation and management.
  • Analysis Queries: SQL queries used for analyzing the dataset, identifying trends, and making business decisions.
  • Documentation: Additional documentation and design schemas related to the project.

Key Features

  • Personalized Recommendations: Utilizes user interaction data to provide personalized product suggestions.
  • Data Analysis: SQL queries designed to analyze customer behavior, product popularity, and sales trends.
  • Inventory Management: Functions and triggers that keep track of product availability and manage inventory efficiently.

Getting Started

To get started with this project, clone this repository and import the SQL scripts into your preferred SQL management tool. The system is built on the following technologies:

  • SQL Server or any compatible SQL database for executing the scripts.
  • [Instructions for setting up the environment, importing the database schema, and any other necessary steps.]

Usage

After setting up your database, you can execute the provided SQL queries to analyze data, manage inventory, and simulate the recommendation system. For detailed instructions on how to use each SQL script, refer to the documentation inside the SQL Scripts folder.

Contribution

Contributions to this project are welcome. To discuss potential improvements or submit a pull request, please refer to the contributing guidelines or contact the project maintainers.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

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