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Content related to Next Enterprise Knowledge Graph Meetup Announced

Webinar: Semantic Graphs in Action – Bridging LPG and RDF Frameworks

As organizations increasingly prioritize linked data capabilities to connect information across the enterprise, selecting the right graph framework to leverage has become more important than ever. In this webinar, graph technology experts from Enterprise Knowledge Elliot Risch, James Egan, David … Continue reading

Knowledge Cast – Paco Nathan, Principal DevRel Engineer at Senzing

Enterprise Knowledge’s Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Paco Nathan, Developer Relations (DevRel) Leader for the Entity Resolved Knowledge Graph Practice at Senzing. He is a computer scientist with over 40 years of tech industry experience … Continue reading

LLM Solutions PoC to Production: From RAGs to Riches (Part 1)

In the past year, many of the organizations EK has partnered with have been developing Large Language Model (LLM) based Proof-of-Concepts (PoCs). These projects are often pushed for by an enthusiastic IT Team, or internal initiative – with the low … Continue reading

Semantic Search Advisory and Implementation for an Online Healthcare Information Provider

The medical field is an extremely complex space, with thousands of concepts that are referred to by vastly different terms. These terms can vary across regions, languages, areas of practice, and even from clinician to clinician. Additionally, patients often communicate … Continue reading

Optimizing Historical Knowledge Retrieval: Leveraging an LLM for Content Cleanup

Enterprise Knowledge (EK) recently worked with a Federally Funded Research and Development Center (FFRDC) that was having difficulty retrieving relevant content in a large volume of archival scientific papers. Researchers were burdened with excessive search times and the potential for knowledge loss … Continue reading

Graph Analytics in the Semantic Layer: Architectural Framework for Knowledge Intelligence

Introduction As enterprises accelerate AI adoption, the semantic layer has become essential for unifying siloed data and delivering actionable, contextualized insights. Graph analytics plays a pivotal role within this architecture, serving as the analytical engine that reveals patterns and relationships … Continue reading

Beyond Traditional Machine Learning: Unlocking the Power of Graph Machine Learning

Traditional machine learning (ML) workflows have proven effective in a wide variety of use cases, from image classification to fraud detection. However, traditional ML leaves relationships between data points to be inferred by the model, which can limit its ability … Continue reading

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