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5 Knowledge graph insights from KMWorld Connect 2021

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At KMWorld Connect 2021, KM industry leaders shared a variety of insights on how to improve customer service, enhance employee efficiency, and drive better decision making from the ever-increasing flow of data into organizations. 

Here are five key insights about knowledge graphs from the 2021 KMWorld Connect presentations:

  1. The ability to explain the results of AI models, and produce consistent results from them, involves modeling real-world events with the adaptive schema consistently provided via knowledge graphs. —Jans Aasman, CEO, Franz Inc
  2. Personal knowledge management can be compared to a knowledge graph. It’s a set of connected type of knowledge objects that have something related between them. —Claude Baudoin, owner and principal, cebe IT and knowledge management
  3. When it comes to relational vs. graph, it’s not an “either/or,” rather, think “AND” (both can work together in harmony). —Art Murray, CEO, Applied Knowledge Sciences
  4. Leveraging the enterprise semantic platform semantic tool suite, its small team delivered an institutional knowledge graph (IKG), a centrally maintained, ever-evolving knowledge graph that identifies and describes JPL’s common concepts and the relationships between them, providing a single source of discovery for users and applications. —Ann Bernath, software systems engineer, NASA Jet Propulsion Laboratory (JPL)
  5. Chatbots can use knowledge graphs and machine learning to work with users to find helpful information and refine searches. —Joseph Hilger, COO, and Neil Quinn, senior consultant, technology solutions, software engineer II, Enterprise Knowledge LLC
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