1 min read
Azure AI Search: Implementing Hybrid Search with Vectors and Keywords
Hybrid search significantly improves retrieval quality for RAG applications by leveraging both semantic understanding and exact keyword matching.
Semantic Search
8 articles
1 min read
Building AI-Powered Search with Azure AI Search and Semantic Ranker
Monitor reranker scores and caption extraction quality. A/B test semantic ranking against pure vector or keyword search to quantify improvements for your…
1 min read
Azure AI Search Updates: January 2024 Features and Capabilities
I've been integrating Azure AI Search into RAG systems; the January 2024 updates simplify common workflows. Below are the changes I judged most impactful…
1 min read
Azure Cognitive Search Vector Search: Building Semantic Search Applications
Vector search enables powerful semantic search capabilities. Tomorrow, I will cover hybrid retrieval patterns in more detail.
1 min read
Semantic Search for Enterprise: Beyond Keyword Matching
Enterprise semantic search transforms how organizations find and use knowledge. By understanding meaning rather than just matching keywords, these systems…
1 min read
Building Semantic Search with Azure OpenAI Embeddings
Embeddings are numerical representations of text that capture semantic meaning. Similar concepts have similar vectors. Azure OpenAI provides the…
1 min read
Building Semantic Search with Azure OpenAI Embeddings
Combine semantic search with keyword matching: Expand queries for better recall: 1. Pre compute embeddings : Don't embed at query time for documents 2. Use…
1 min read
Semantic Search in Azure Cognitive Search
Semantic search dramatically improves search relevance by understanding user intent rather than just matching keywords.