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Floating Cubes
Problem

Poor quality automated content tagging

This is a common problem in information management, and a challenge in high-value digital asset products and services.
Improved by these Interventions
Launching a new Content Tagging Strategy
Designing and delivering a new content tagging strategy involves a spread of cultural and technological elements. This technology intervention involves tagging strategy, governance, and tagging templates.
Technologies used
Metadata Management Software as a Service (SaaS)
KGaaS - Knowledge Graph as a Service
Knowledge Graphs
Library Science
Information Architecture (IA)
Knowledge Graph Creation Tools
Domain-Driven Design (DDD)
Inhibits these Capabilities
High quality metadata
Metadata that is accurate and supports disambiguation and business workflows, as well as leveraging the assets in business product scenarios.
Leads to these Problems
Low value content tagging
Caused by these Problems
NLP or NER auto tagging predicts too many tags to be useful
FAQs
What are the top 5 problems in Automated Content Tagging?
  1. The tags are too generic.
  2. The tags are not relevant.
  3. The tags are not consistently accurate.
  4. The training cycles are too slow.
  5. The Data Science overhead is too large.