Enhancing Document Retrieval with Contextual Overlapping Windows

Improved accuracy in document retrieval with context enrichment for more relevant results.

Enhanced semantic understanding using OpenAI embeddings for better query alignment.

Efficiently processed large documents using chunking and overlap.

FAISS vectorstore optimized search speed, enabling fast retrieval in large datasets.

Provided coherent answers by retrieving neighbouring context alongside relevant chunks.

Demonstrated the benefits of contextual information over traditional methods.

Achieved scalable retrieval for large datasets without performance issues.

Enhanced query understanding with neighboring chunk enrichment.

Fine-tuned system parameters for better relevance and accuracy.

Enabled real-time updates to ensure the system stays current with new documents.