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Content related to Ivanov and Midkiff to Speak at the Cognitive Computing Summit 2018 in Boston, MA

Enhancing Insurance Fraud Detection through Graph-Based Link Analysis

A national agency overseeing insurance claims engaged EK to advise on developing and implementing graph-based analytics to support fraud detection. EK applied key concepts such as knowledge graphs, graph-based link analysis for detecting potentially suspicious behavior, and the underlying technology architecture required to instantiate a fully functional solution at the agency to address client challenges. Continue reading

Top Semantic Layer Use Cases and Applications (with Real World Case Studies)  

Today, most enterprises are managing multiple content and data systems or repositories, often with overlapping capabilities such as content authoring, document management, or data management (typically averaging three or more). This leads to fragmentation and data silos, creating significant inefficiencies. … Continue reading

Enhancing Taxonomy Management Through Knowledge Intelligence

In today’s data-driven world, managing taxonomies has become increasingly complex, requiring a balance between precision and usability. The Knowledge Intelligence (KI) framework – a strategic integration of human expertise, AI capabilities, and organizational knowledge assets – offers a transformative approach … Continue reading

Why Your Taxonomy Needs SKOS 

Taxonomies are a valuable tool for capturing semantic context, but their full value can only be realized when they’re represented in a standardized format. This infographic introduces SKOS (Simple Knowledge Organization System) and demonstrates how your organization’s taxonomies can reach their full potential. Continue reading

Enterprise AI Architecture Series: How to Inject Business Context into Structured Data using a Semantic Layer (Part 3)

Introduction AI has attracted significant attention in recent years, prompting me to explore enterprise AI architectures through a multi-part blog series this year. Part 1 of this series introduced the key technical components required for implementing an enterprise AI architecture. … Continue reading

How a Semantic Layer Transforms Engineering Research Industry Challenges

To drive future innovation, research organizations increasingly seek to develop advanced platforms that enhance the findability and connectivity of their knowledge, data, and content–empowering more efficient and impactful R&D efforts. However, many face challenges due to decentralized information systems, where … Continue reading