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We have created an AI-powered platform dedicated to identifying and verifying the authenticity of restaurant reviews. On this website, users can:
Check Review Authenticity - Input review text to get an authenticity score.
Browse Restaurant Information - View ratings, reviews, and word clouds for specific restaurants.
Analyze Review Trends - Understand overall restaurant ratings through visualized data.
- Review Analysis:
- Input review text for authenticity analysis
- Display authenticity score for reviews
- Restaurant Information:
- Show restaurant location, ratings, and reviews
- Generate word clouds from reviews
- Display restaurant's percentile ranking among all ratings
- Map Functionality:
- Display restaurant locations
- Interface:
- Responsive design
- Intuitive user interface
- Automated Web Scraping:
- Regularly collect new restaurant reviews from popular platforms
- Update database with fresh review data
- Ensure up-to-date analysis and trends
- React.js, Next.js
- UI components: shadcn-ui
- Map functionality: @vis.gl/react-google-maps
- Flask API
- Machine Learning model: PyTorch
- Data processing: pandas, numpy
- Natural Language Processing: googletrans, wordcloud
- Web scraping: Beautiful Soup, Selenium
- Code formatting and linting: eslint, prettier
- Type checking: typescript
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Clone this repository:
git clone https://github.com/guan404ming/certif-eye.git cd certif-eye
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Set up environment variables in frontend:
cd frontend
- Create a
.env
file in the frontend root - Add necessary environment variables (e.g., database URL, API keys, etc.)
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Install and run the development servers:
- Frontend:
cd frontend bun install bun run next-dev
- Backend:
cd backend pip3 install -r requirements.txt python3 -m flask --app api/index run -p 5328
- Frontend:
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Open http://localhost:3000 with your browser to see the result.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.