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Content related to Knowledge Graphs for Search and Discovery

Content Silos: Causes, Problems, and Solutions

Organizations are producing exponentially more content than ever before. In most businesses today, every employee is a content creator which has led to multiple, uncoordinated content management systems (CMS). Siloed systems cause content management issues such as duplication of content, … 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

Inside the Intranet – ESEO

Optimizing the Findability of your Content on an Intranet In any organization it’s well known that inefficiencies and/or waste, especially wasted time, can significantly impact the bottom line. This is a key driver in the explosion of artificial intelligence (AI), … Continue reading

SharePointSaga Episode 3: Upgrading and Migrating Your SharePoint System, Pt. 2 (Revenge of the Steps)

“So who talks first, you talk first, I talk first?” In the last episode, I explored important considerations when migrating/upgrading SharePoint. This episode highlights the specific steps of migrating/upgrading between particular versions of SharePoint, especially for on-premise instances. Before outlining … 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