Movie Minds is a web application that helps users explore trending and upcoming movies while connecting with others who share similar movie preferences. With personalized recommendations, social networking features, and a user-friendly interface, Movie Minds creates an engaging platform for movie enthusiasts.
- Secure login and signup using JWT (JSON Web Token) for authentication.
- Two-step signup process:
- Provide basic details like name, email, and password.
- Enter movie preferences and social links for personalization.
- Welcome Page: Engaging design featuring a video background and options to sign up or log in.
- Browse Page: Displays popular movies fetched from the TMDB API.
- Trending Page: Lists trending movies along with their ratings.
- Coming Soon Page: Highlights movies scheduled for upcoming release.
- Profile Page: Allows users to view, update, or delete their profiles.
- Connection Page: Matches users based on similar movie preferences with options to connect via social media.
- Powered by ML Algorithms:
- Uses Cosine Similarity to recommend movies based on user searches.
- Features include:
- Suggesting movies similar to the one searched.
- Displaying detailed information about a movie.
- Browsing through a large movie collection.
- Built using libraries like Sklearn and NLTK.
- Model-View-Controller (MVC) Pattern:
- Model: MongoDB for managing user profiles, preferences, and connections.
- View: React.js for building dynamic and interactive user interfaces.
- Controller: Express.js to handle backend logic and API connections.
- Custom CSS for unique, user-friendly page designs.
- Flexible and responsive UI for desktop users, with plans for mobile optimization.
- Frontend: React.js
- Backend: Node.js with Express.js
- Database: MongoDB
- APIs: TMDB API for fetching movie data
- Authentication: JWT for secure user login
- Recommendation Engine: Python libraries (Sklearn, NLTK) for ML algorithms
- Data Privacy:
- Secure password encryption and token-based authentication.
- Option for users to delete their profiles and data.
- Bias Mitigation:
- Efforts to use diverse datasets and algorithms for unbiased recommendations.
- Chat Feature: Enable direct conversations between users about favorite movies.
- Group Functionality: Create groups based on shared movie preferences.
- Improved Recommendations: Expand dataset and refine algorithms for more diverse suggestions.
- Mobile Optimization: Enhance accessibility on mobile devices.
- User Feedback Integration: Allow users to rate recommendations for tailored results.
- Node.js and npm installed.
- MongoDB server running locally or via a cloud provider.
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Clone the repository:
git clone https://github.com/munavarhs/MovieMinds.git
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Download the files from the following link: Google Drive
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Create a folder named
Filesin the same path whereclientandserverexist, and copy the.pklfiles from the downloaded folder into it. -
Update your
Login.cssfile as needed. Use the reference image below for guidance:
- Update your
SignupStep1.cssfile as needed. Use the reference image below for guidance:
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Download the video from this link and paste it into the
client/src/assets/videosfolder. -
Start the client by running the following command:
npm start- Start the server by running the following command:
nodemon index.js- Start the recommendation engine by running the following command:
streamlit run MovieMinds.py- User Registration
1.1 Preconditions
- User must have access to the application.
- A valid email address is required.
1.2 Main Flow
- User accesses the registration page and provides the required information: first name, last name, email, and password [S1].
- User sets their movie preferences and social media URL [S2].
- The system validates the input and registers the user [S3].
1.3 Subflows
- [S1] User navigates to the signup page and enters their information in the provided fields.
- [S2] User selects movie preferences and provides a social media URL.
- [S3] System validates the input fields, saves the data, and confirms registration.
1.4 Alternative Flows
- [E1] User provides an already registered email. The system displays an error message.
- User Login
2.1 Preconditions
- User must be registered in the system with a valid email and password.
- The application must be running and accessible.
2.2 Main Flow
- User navigates to the login page and enters their email and password [S1].
- The system validates the credentials [S2].
- Upon successful validation, the user is granted access to their dashboard [S3].
2.3 Subflows
- [S1] User enters their registered email and password into the login form.
- [S2] System checks the entered credentials against the stored database records.
- [S3] System redirects the user to their dashboard with a welcome message.
2.4 Alternative Flows
- [E1] User enters incorrect credentials. The system displays an error message.
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Movie Exploration
Users can browse through a variety of movies, including trending and upcoming releases, to discover their next favorite movie. -
Movie Recommendations
The system provides tailored movie recommendations based on user preferences, content, genres, production companies, keywords, and cast. -
Social Connections
Users can connect with others who share similar movie interests, creating a community for movie discussions. -
Profile Management
Users can view and manage their profiles, updating preferences as needed to refine recommendations. -
Detailed Movie Information
Users can access detailed descriptions of movies, including cast, synopsis, and other relevant details. -
Insights into Upcoming Releases
Stay informed about movies that are soon to be released with the "Coming Soon" page. -
Trending Movies
Quickly identify trending movies to stay up-to-date with popular choices. -
Interactive UI
Enjoy a user-friendly interface with smooth navigation and visually appealing design, ensuring an enjoyable experience.
Test cases can be found under the following path:
client/src/pages