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Content related to Enterprise AI Meets Access and Entitlement Challenges: A Framework for Securing Content and Data for AI

The Role of Taxonomy in Labeled Property Graphs (LPGs) & Graph Analytics

Taxonomies play a critical role in deriving meaningful insights from data by providing structured classifications that help organize complex information. While their use is well-established in frameworks like the Resource Description Framework (RDF), their integration with Labeled Property Graphs (LPGs) … Continue reading

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

Semantic Layer Strategy for Linked Data Investigations

A government organization sought to more effectively exploit their breadth of data generated by investigation activity of criminal networks for comprehensive case building and threat trend analysis. EK engaged with the client to develop a strategy and product vision for their semantic solution, paired with foundational semantic data models for meaningful data categorization and linking, architecture designs and tool recommendations for integrating and leveraging graph data, and entitlements designs for adhering to complex security standards. 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