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Movie-recommendation-system

MIT License


MOVIE RECOMMENDATION SYSTEM

An awesome UI software which can recommend you movies,webshows!!
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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgements

About The Project

A recommendation system is a type of information filtering system which attempts to predict the preferences of a user, and make suggests based on these preferences. There are a wide variety of applications for recommendation systems. These have become increasingly popular over the last few years and are now utilized in most online platforms that we use. The content of such platforms varies from movies, music, books and videos, to friends and stories on social media platforms, to products on e-commerce websites, to people on professional and dating websites, to search results returned on Google. Often, these systems are able to collect information about a users choices, and can use this information to improve their suggestions in the future. In the browser, if we search movie name it will give similar movies related to that input movie. This is done by three recommendation engine such as popular based recommendation engine, content-based recommendation engine, collaborative filtering based recommendation engine.

The popular based recommendation engine is nothing but trending list on YouTube, Netflix, etc. They will keep on tracking the video views and update the on-trending list. The content-based recommendation engine is taking the input from the user and give a similar rank list based on the content related to the input movie. In this project, the content-based recommendation engine is used. The collaborative filtering-based recommendation engine is first search the similar user based on their activity and behavior and if the first user and second user have seen the same movie and if the first user has seen the new movie but if the second user not. It recommends new movies to a second user and vice-versa

Built With

This section consist of list of major frameworks that were used in our project. Additionally add-ons/plugins are mentioned in the acknowledgements section. Here are a few examples.

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

  • npm 
    npm install npm@latest -g

Installation

  1. Get a free API Key at https://example.com
  2. Clone the repo 
    git clone https://github.com/your_username_/Project-Name.git
  3. Install NPM packages 
    npm install
  4. Enter your API in config.js 
    const API_KEY = 'ENTER YOUR API';

Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Your Name - @your_twitter - [email protected]

Project Link: https://github.com/your_username/repo_name

Acknowledgements