Enhanced Data Augmentation and Synthesis

Project Overview

A sophisticated data augmentation system that uses Retrieval-Augmented Generation (RAG) to enhance and synthesize review datasets. The system leverages FAISS for efficient vector storage and retrieval, combined with Sentence-BERT for generating high-quality semantic embeddings.

Technologies Used

Key Features

• Automated review dataset enhancement
• FAISS-based vector similarity search
• Sentence-BERT semantic embeddings
• RAG pipeline for content generation
• Quality assessment metrics
• Scalable processing pipeline

Technical Challenges

• Maintaining review authenticity in generated content
• Optimizing FAISS indexing for large datasets
• Ensuring semantic coherence in augmented data
• Balancing augmentation quantity with quality

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