Knowledge mining

Knowledge mining refers to an emerging category of AI designed to simplify the process of accessing the latent insights contained within structured and unstructured data. Knowledge mining defines the process of using an AI pipeline to discover hidden patterns and actionable information from sets of structured and unstructured data in a scalable way. Knowledge mining includes a complex logical understanding and can connect information streams to form real world business insights.

Azure AI Search provides secure information retrieval at scale over user-owned content in traditional and conversational search applications. It offers capabilities such as vector indexing and queries, scoring, faceting, suggestions, synonyms, and geo-search to provide a rich user experience. Azure AI Search is also the only cloud search service with built-in knowledge mining capabilities. Azure AI Search acts as the orchestrator for your knowledge mining enrichment pipeline by following the steps to ingest, enrich, and explore and analyze.

Key scenarios for knowledge mining include:

  • Digital content management: Help customers consume content more quickly by providing them relevant search results in your content catalog.
  • Customer support and feedback analysis: Quickly find the right answer in documents and discover trends of what customers are asking for to improve customer experiences.
  • Data extraction and process management: Accelerate processing documents by extracting key information and populating it in other business documentation.
  • Technical content review and research: Quickly review documents and extract key information to make informed decisions.
  • Auditing and compliance management: Quickly identify key areas and flag important ideas or information in documents.

Knowledge mining solutions checklist

Next steps

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