Portfolio Details
Semantic Book Recommendation System
An intelligent book recommendation system that analyzes book descriptions, categories, and emotional tone (happy, sad, etc.) to suggest personalized books for users.
Uses semantic analysis and NLP to understand book content and user preferences, providing recommendations based on mood, genre, and description.
Accurately detecting emotional tone and semantic meaning from book descriptions and matching them to user moods and interests.
Implemented NLP models and a semantic search engine to recommend books based on user-selected mood, category, and description similarity.
Key Features
- Mood-based Recommendations
- Category Filtering
- Semantic Search
- Personalized Suggestions
- Real-time Updates
- Multi-device Support