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A Conversation about Knowledge Graphs vs Structured Content for Enterprises Part 2

Aug 12, 2022
The podcast discusses knowledge graphs and structured content, including the definition of knowledge graphs and their importance. It also explores the significance of relationships in knowledge graphs and the challenges of implementing them in enterprises. The podcast emphasizes the need for a knowledgeable evangelist and the power of a proof of concept. It concludes with a discussion on the future of knowledge graphs and the need for improved accessibility.
51:57

Podcast summary created with Snipd AI

Quick takeaways

  • Structured content enables create once, publish everywhere functionality and personalized experiences, while knowledge graphs facilitate the flexible mixing and matching of content from different sources.
  • Overcoming challenges in implementing knowledge graphs involves educating stakeholders, conducting proof of concepts, starting with clearly defined use cases, and taking a structured approach to content modeling.

Deep dives

Benefits of Knowledge Graphs and Structured Content

Knowledge graphs and structured content offer numerous benefits for enterprises. Structured content allows for the organization and separation of content into its constituent parts, enabling create once, publish everywhere functionality and personalized experiences. Knowledge graphs, on the other hand, provide a knowledge base of intelligently connected machine-readable facts about things from one or more sources. By using knowledge graph technology and standards, enterprises can organize and stitch together information from different sources, allowing for the flexible mixing and matching of content. This facilitates the creation of personalized experiences and enables the integration of data from various repositories. By leveraging the power of semantic technology, knowledge graphs make it easier to control and combine content from multiple sources, enhancing content organization, management, and discovery.

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