Nomnom is a web application that combines sentiment analysis, machine learning, and collaborative filtering to help users plan meals and dining experiences based on their emotions, events, or preferences. The app suggests restaurants and dishes that align with the user's mood, budget, dietary requirements, and more.
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Emotion Analysis: Nomnom uses sentiment analysis to determine the user's current emotional state based on their input.
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Restaurant Recommendations: The app provides restaurant recommendations based on the user's mood, budget, aesthetics, type, and diet.
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Personalization: Users can input dietary preferences, allergies, and food restrictions to receive tailored recommendations.
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Interactive User Interface: The web-based user interface allows for an engaging and interactive experience.
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Feedback Mechanism: Users can provide feedback on recommended restaurants, helping improve future suggestions.
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Machine Learning Enhancement: Over time, the app learns from user interactions and feedback to refine its recommendations.
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Fill out the form with your current mood, hunger level, preferences, budget, restaurant aesthetics, type, and diet.
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Submit the form to receive restaurant recommendations that match your input.
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Click on the "Show Recommendations" button to view the recommended restaurants.
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Explore the recommended restaurants and make your dining choice!
Happy dining with Nomnom! 🍽️