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Content related to Expert Analysis: How Does My Organization Use Auto-tagging Effectively? Part Two

Making Search Less Taxing: Leveraging Semantics and Keywords in Hybrid Search

Explore how Tax Analysts, the nonpartisan nonprofit behind Tax Notes, upgraded its search functionality to help subscribers both easily find information and discover unexpected, relevant content. At KMWorld 2025, Chris Marino of Enterprise Knowledge partnered with Jaime Martin, Senior Product Manager … Continue reading

Optimizing Historical Knowledge Retrieval: Extracting Knowledge by Making Connections 

A financial services firm built a mature graph data ecosystem, but the graph database they selected originally did not scale as multiple business-critical solutions relied on graph data. As application and business teams across multiple stakeholder groups expanded usage … Continue reading

Taxonomy Alignment for SDG Tagging

In the session  “Utilizing Taxonomies to Meet UN SDG Obligations“ co-presented at KMWorld 2025 on November 17th, Enterprise Knowledge’s Ben Kass and ASHA’s Mike Cannon discuss how they structured taxonomies within an ongoing auto-tagging implementation to serve content management and … Continue reading

Taxonomist Role in the New World of Generative AI

We have been at the forefront of implementing generative technologies to augment traditional taxonomy workflows offering new capabilities for content modeling, classification, and semantic enrichment. This raises an important question for practitioners: What are the implications of Generative AI for … Continue reading

A Healthier Knowledge Platform: Taxonomy Principles to Support Knowledge Management at a Not-for-Profit

Would your organization benefit from “healthier” knowledge management practices? Learn more about how the YMCA of the USA improved the health of key internal tools.  During their presentation, “Taxonomy Principles to Support Knowledge Management at a Not-for-Profit” at KMWorld’s Taxonomy … Continue reading

How to Design Taxonomies that Reflect Organizational Differences, For Humans and AI

One of the key steps to prepare your content and data for AI is developing taxonomies that identify, organize, and define the terms used in the organization in order to better structure and contextualize knowledge assets for use in AI … Continue reading

How Taxonomies and Ontologies Enable Explainable AI

Taxonomy and ontology models are essential to unlocking the value of knowledge assets. They provide the structure needed to connect fragmented information across an organization, enabling explainable AI. As part of a broader Knowledge Intelligence (KI) strategy, these models help … Continue reading