Journal Recommendation System

Welcome to the Journal Recommendation System! This system sends personalized journal papers to users based on their interests.

Here is a video to demonstrate how to run this project is given below:

Features

• User registration and interest configuration
• Weekly email updates with relevant journal papers
• Automatic mailing system
• User-friendly interface for managing interests

Prerequisites

Before running the project, ensure you have the following installed:

• Node.js
• npm
• SQLite
• Node.js installed
• API keys for Springer and IEEE APIs (update the .env file)
• Gmail account credentials (update the .env file)
• Gmail account app passwords for EMAIL_PASS

Installation

1. Clone the repository:

     git clone https://github.com/your-username/your-repo.git   

or you can download it in zip format.

2. Set up environment variables:

-Enter your sender's Mail_ID -Enter your app password -Then enter your Springer_API_key for example

    EMAIL_USER = your-email@gmail.com
    EMAIL_PASS = your_app_password
    SPRINGER_API_KEY = springer-api-key(23782147123)

3.Install the dependencies:

After updating the env file install the dependencies by entering entering the given code in server.js file terminal

  npm install

After installing the dependencies successfully run the application by

  npm start

The application should now be running at http://localhost:3000.

4. User registration:

In the application the users will enter their mail_id and thier interests

After registering the users detials will be saved in the database

5. Run the python script:

After registering run the python in your code editor
After executing the application it will send mail to the user according to their interests.

Usage

1.Open your web browser and navigate to http://localhost:3000. 2.Follow the on-screen instructions to register your interests. 3.You will receive weekly email updates with journal papers related to your interests. 4.This can be implemented more in colleges and universities

License

This project is licensed under the MIT License.