Content related to A Data Scientist Perspective on Knowledge Graphs (Part 1): the Data-Driven Challenge
The Role of Ontologies with LLMs
In today’s world, the capabilities of artificial intelligence (AI) and large language models (LLMs) have generated widespread excitement. Recent advancements have made natural language use cases, like chatbots and semantic search, more feasible for organizations. However, many people don’t understand … Continue reading
Case Studies: Applications of Data Governance in the Enterprise
Thomas Mitrevski, Senior Data Management and Governance Consultant and Lulit Tesfaye, Partner and Vice President of Knowledge and Data Services presented “Case Studies: Applications of Data Governance in the Enterprise” on December 6th, 2023 at DGIQ in Washington D.C. In … Continue reading
Scaling Knowledge Graph Architectures with AI
Sara Nash and Urmi Majumder, Principal Consultants at Enterprise Knowledge, presented “Scaling Knowledge Graph Architectures with AI” on November 9th, 2023 at KM World in Washington D.C. In this presentation, Sara and Urmi defined a Knowledge Graph architecture and reviewed … Continue reading
4 Critical Elements of a Successful Data Governance Program
Without a strong data governance framework, maintaining your organization’s data can become an unwieldy challenge: with unclean, decentralized data, staff may begin to lose trust and confidence in the information they are working with. If you’re unsure where to start, … Continue reading
Knowledge Portal Architecture Explained
At its core, a Knowledge Portal consists of five components: Web UI, API Layer, Enterprise Search Engine, Knowledge Graph, and Taxonomy/Ontology Management System. Continue reading
KM Fast Track to Search-Focused AI Solutions
In today’s rapidly evolving digital landscape, the ability to quickly locate and connect critical information is key to organizational success. As organizations struggle with ever-expanding datasets and information silos, the need for effective search-focused artificial intelligence (AI) solutions becomes vital. … Continue reading
Exploring Vector Search: Advantages and Disadvantages
The search for information is at the core of enhancing productivity and decision-making in the enterprise. In today’s digital age, searching for information has become more intuitive. With just a few clicks, we can explore vast knowledge and gain once-inaccessible … Continue reading
Semantic LLM Accelerator
With the right context, Large Language Models (LLMs) can be a powerful tool to accelerate enterprise digital transformations. Knowledge graphs provide that enterprise context, giving organizations the ability to understand and trust LLMs to take advantage of their powerful applications. … Continue reading
5 Steps For Building Your Enterprise Semantic Recommendation Engine
In today’s digital landscape, where content overload is a constant challenge, recommendation engines (also known as personalized content recommenders, or just “recommenders”) have emerged as powerful solutions that help users cut through the noise and discover relevant information. These intelligent … Continue reading
How a Knowledge Graph Supports AI: Technical Considerations
In 2023, ChatGPT’s explosive popularity made Artificial Intelligence (AI) language models a household name. In essence, these models are a key component of natural language processing (NLP), a field of AI, focused on enabling computers to understand and generate human … Continue reading