Enhancing Document Retrieval with Contextual Overlapping Windows
Improve document retrieval with contextual overlapping windows, PDF processing, text chunking, FAISS, and OpenAI embeddings for more coherent search results.
$10 USD
$5.00 USD
Project Outcomes
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Improved accuracy in document retrieval with context enrichment for more relevant results.
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Enhanced semantic understanding using OpenAI embeddings for better query alignment.
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Efficiently processed large documents using chunking and overlap.
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FAISS vectorstore optimized search speed, enabling fast retrieval in large datasets.
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Provided coherent answers by retrieving neighbouring context alongside relevant chunks.
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Demonstrated the benefits of contextual information over traditional methods.
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Achieved scalable retrieval for large datasets without performance issues.
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Enhanced query understanding with neighboring chunk enrichment.
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Fine-tuned system parameters for better relevance and accuracy.
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Enabled real-time updates to ensure the system stays current with new documents.
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