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Industry Leaders on AI & KM: Are Knowledge Graphs the Way

Presentation Slides
Our industry leaders share case studies of how knowledge graphs are revolutionizing KM programs. Popov discusses organizing and classifying information through a knowledge graph and how generative AI and ChatGPT might integrate into your organization to create taxonomies to classify data, ensuring that you are getting access to the right data in the right format; turning buzzwords into action; and unleashing the power of your data and its insights. He shares case studies to illustrate how to link diverse data, index it for semantic search, and enrich it with text analysis to build and scale large knowledge graphs across any industry.

Hayden discusses supporting green strategies with enterprise knowledge graphs, an ideal platform to use in the environmental, social and governance (ESG) domain. Linking all the data for the enterprise makes it easier, starting with the domain model and building it with NLP and machine learning. He shares how one organization is using this technique for an enterprise recommender system. Kasenchak focuses on graph-based content management. He discusses how when your CMS and tag management tools are only lightly integrated, tagging terms get divorced from the rich semantic environments we spend so much time modeling. He suggests to get better results with structured content, we need to think of content tags as objects in the same information ecosystem, not just words in a field. He describes how a large enterprise is moving towards graph-based structured content management so its systems can take full advantage of semantic relationships and attributes, enabling better discoverability and content analytics.

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KMWorld 100 COMPANIES That Matter in Knowledge Management

KMWorld Trend-Setting Product of 2016, 2017 and 2018