Gartner Research

Automatic Classification and Tagging Make Metadata Manageable for ECM and Search

Published: 05 August 2015

ID: G00277035

Analyst(s): Darin Stewart


Metadata is central to effective enterprise content management and search, but remains impractical for many organizations. Rule-based and machine-learning-based automation can help IT professionals not only jump-start a tagging initiative, but also sustain it long term.

Table Of Contents


  • Obstacles to Effective Metadata
    • Retooling the Environment and the Content It Contains
    • Content Creators and End Users
  • Approaches to Automation
    • Rule-Driven Metadata Automation
    • Machine Learning and Unsupervised Classification
    • Hybrid Automation
  • Metadata Beyond the Tombstone
  • Strengths
    • Reduces Effort for Content Creators and End Users
    • Improves Quality and Consistency of Metadata and Content
    • Expands the Scope of What Metadata Is and How It Can Be Used
  • Weaknesses
    • Reduces, but Does Not Eliminate, Human Effort and Involvement
    • Requires a Specialized Skill Set
    • May Require New Applications or Additional ECM Modules


  • Define a Foundational Metadata Framework
  • Develop or Acquire Managed Vocabularies for Critical Elements
  • Start With Rule-Driven Automation
  • Test an Automated Rule Generation and Categorization Tool
  • Feedback on This Document

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