Auto-Classification for the Enterprise: When to Use AI vs. Semantic Models

Auto-classification is a valuable process for adding context to unstructured content. Nominally speaking, some practitioners distinguish between auto-classification (placing content into pre-defined categories from a taxonomy) and auto-tagging (assigning unstructured keywords or metadata, sometimes generated without a taxonomy). In this article, I use ‘auto-classification’ in the broader sense, encompassing both approaches. 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

Natural Language Processing and Taxonomy Design

Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that processes and analyzes human language found in text. Some of the exciting capabilities that NLP offers includes parsing out the significant entities in content through a statistical analysis … Continue reading

4 Steps to Content Auto-Classification with High Accuracy

As technologies evolve, we have seen the rise of auto-tagging, auto-classification, and auto-categorization tools that attempt to take over the task for describing the content we create. These tools apply metadata tags automatically so we don’t have to. Yet, in … Continue reading