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Content related to Thomas Mitrevski and Lulit Tesfaye to Speak at Data Governance and Information Quality (DGIQ) Conference 2023

A Course Recommendation System – Based on a Knowledge Graph

The Challenge A healthcare workforce solutions provider wanted to increase engagement and learning outcomes across their learning platform as part of an initiative to grow interactive and adaptive learning capabilities using cutting edge knowledge management and natural language processing techniques. … Continue reading

What I’m Looking Forward to Learning at SEMANTiCS Austin 2020

SEMANTiCS Austin 2020 is the inaugural SEMANTiCS U.S. conference that will bring together knowledge graphs, ontologies, and Enterprise AI. These topics, among others, are of particular interest to my work in search and semantics, and I am excited to see … Continue reading

What’s the Difference Between an Ontology and a Knowledge Graph?

As semantic applications become increasingly hot topics in the industry, clients often come to EK asking about ontologies and knowledge graphs. Specifically, they want to know the differences between the two. Are ontologies and knowledge graphs the same thing? If … Continue reading

What is Artificial Intelligence (AI) for the Enterprise?

Artificial intelligence (AI) is set to be the key source of transformation, disruption, and competitive advantage in today’s fast-changing economy. Gartner estimates that AI will create $2.9 trillion in business value and 6.2 billion hours of worker productivity in 2021. … Continue reading

Knowledge Graphs Creating a Connected Search Experience

This presentation, delivered by Joseph Hilger of Enterprise Knowledge at KMWorld 2019 in Washington, D.C., defines knowledge graphs, explores how they are implemented, and outlines how they can be used to enhance enterprise search. Knowledge graphs are changing the way search … Continue reading

The 5 Key Components of a Semantic Search Experience

Semantic Search extends meaning and context to your otherwise run-of-the-mill search results. This future-ready phase of search seeks to apply machine-driven understanding of user intent, query context, and the relationships between words. We broke down the primary elements that make … Continue reading