This script is written for AI-powered matchmaking system that intelligently pairs users based on their textual responses. It uses Word2Vec embeddings to understand the semantic meaning of responses and cosine similarity to determine how closely two users' responses align.
Friendship & Social Networking – Matching users with similar interests.
✔ Natural Language Understanding – Uses Word2Vec embeddings to capture the meaning of user responses.
✔ Smart Matching – Employs cosine similarity to rank user compatibility.
✔ Scalable Architecture – Can be integrated into web apps, chatbots, or mobile applications.
✔ Customizable Matching Criteria – Can be fine-tuned based on specific requirements.
- Python – Core programming language
- Gensim – For training and using Word2Vec embeddings
- NumPy – For vectorized operations
- Scikit-learn – For cosine similarity calculations
- Pandas – For handling and processing user data
git clone https://github.com/Nitika13/Matchmaking.git
cd Matchmaking