DataMap_Neo.md

Project-name

Team name: Team Neo

Team members

• Pratiksha Sankhe - [email protected]
• Jash Shah - [email protected]
• Dushant Harinkhede - [email protected]
• Naman Kothari - [email protected]

Mentors

• Ravi Maurya
• Utsav Khatu
• Vishad Dange

Description

Data-Map is a movie recommendation website which can help users discover movies which are similar to a particular movie the user enters, but with a twist! Instead of simply listing them it creates a Map of the recommendations.

• The Map is displayed with the user entered title at the centre and the reccomended movies spread around it.
• Their distance from the centre indicating their degree of similarity.

The user can also navigate to maps of the reccomended movies by just clicking on them.

• The ML model uses Cosine Similarity and K-Nearest Neighbours algorithms to predict the movies.
• Alchemy.JS library is used for displaying the data in map format.
• HTML/CSS/JS and React are used for building the UI and other features of the website.
• TMDB API is used for displaying movie info.
• GitHub repo link: GitHub
• Drive link: Drive
• Website link: Website link here

Technology stack

Tools and technologies that you learnt and used in the project.

1. JavaScript (Alchemy.JS for creating maps)
2. HTML/CSS
3. Pyhton(Pandas, Sklearn)
4. React
5. Flask

Progress

• Design and Train ML Model.
• Design Website UI.
• Setup API services to display info of Movies.
• Learn Alchemy.JS Library for creating Map.
• Create Map using Alchemy.
• Setup API using Flask for fetching ML data.

Project Setup

File Structure

📦Movie-map
 ┣ 📂public
 ┃ ┣ 📜favicon.ico
 ┃ ┣ 📜index.html
 ┃ ┣ 📜manifest.json
 ┃ ┗ 📜robots.txt
 ┣ 📂src
 ┃ ┣ 📂Components
 ┃ ┃ ┣ 📂About
 ┃ ┃ ┃ ┣ 📜about.css
 ┃ ┃ ┃ ┗ 📜about.js
 ┃ ┃ ┣ 📂Footer
 ┃ ┃ ┃ ┣ 📜Footer.css
 ┃ ┃ ┃ ┗ 📜Footer.js
 ┃ ┃ ┣ 📂Home
 ┃ ┃ ┃ ┗ 📜Home.js
 ┃ ┃ ┣ 📂Movie
 ┃ ┃ ┃ ┣ 📂ContentModal
 ┃ ┃ ┃ ┃ ┣ 📜ContentModal.css
 ┃ ┃ ┃ ┃ ┗ 📜ContentModal.js
 ┃ ┃ ┃ ┗ 📂SingleContent
 ┃ ┃ ┃ ┃ ┣ 📜SingleContent.css
 ┃ ┃ ┃ ┃ ┗ 📜SingleContent.js
 ┃ ┃ ┣ 📂Navbar
 ┃ ┃ ┃ ┣ 📜Navbar.css
 ┃ ┃ ┃ ┗ 📜Navbar.js
 ┃ ┃ ┣ 📂page_2
 ┃ ┃ ┃ ┗ 📜page_2.js
 ┃ ┃ ┗ 📂Search bar
 ┃ ┃ ┃ ┣ 📜Search.css
 ┃ ┃ ┃ ┗ 📜Search.js
 ┃ ┣ 📂config
 ┃ ┃ ┗ 📜config.js
 ┃ ┣ 📜App.css
 ┃ ┣ 📜App.js
 ┃ ┣ 📜App.test.js
 ┃ ┣ 📜index.js
 ┃ ┣ 📜reportWebVitals.js
 ┃ ┗ 📜setupTests.js
 ┣ 📜.gitignore
 ┣ 📜package-lock.json
 ┗ 📜package.json

In the project directory, you can run:

npm start

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

npm test

Launches the test runner in the interactive watch mode.
See the section about running tests for more information.

npm run build

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes.
Your app is ready to be deployed!

See the section about deployment for more information.

npm run eject

Note: this is a one-way operation. Once you eject, you can’t go back!

If you aren’t satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.

Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.

You don’t have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.

Usage

1. The user enters a movie, to which they want to find similar movies.
2. The website processes the movie through its ML model and responds with movies whcih are most similar to the one entered(in terms of genre,cast,crew,rating,etc.).
3. These recommendations are then displayed in a Map format with the user's choice at the centre.
4. The recommendations are spread around with their distance from the central movie indicating their degree of similarity.

Applications

It provides an intuative visualtization of recommendations which saves users from having to go through numbers,graphs,movie data temselves.

Future scope

• This concept can also be extended to other media recommendation systems like books, music, games, etc.
• Giving users an ability to make a wishlist and then tailor the reccomedations further based on the movies in said wishlist.

Screenshots

1. Landing Page

2. Movie Description Template

3. Map Template