Taxonomies play a crucial role in organizing and classifying information for media organizations. Traditional taxonomies have long been the standard method for structuring content and making it more manageable to organize and find related articles; however, creating and maintaining an effective taxonomy comes with a new set of challenges in the fast-paced world of media.

What is a traditional taxonomy in media?

A traditional taxonomy in media is a hierarchical classification system that organizes information into categories based on their attributes. It is characterized by rigorous categorization rules, mutually exclusive classification, and exhaustive granularity. 

But while traditional taxonomy can be effective for organizing content within a media organization, their rigidity and hierarchy pose challenges. These include difficulty adapting to new content types, complex and time-consuming management, overlapping content categories, and poor scalability in the face of rapidly changing news cycles and content trends.

Manual tagging is also time consuming and inconsistent. The high volume and rapid production of content in media organizations means that authors and editors are left to apply keywords at their own discretion. As topics shift or expand, these tags get stale and some of your best content gets buried.

AI is revolutionizing taxonomy

AI tools can suggest taxonomy structures, maintain taxonomies as content evolves, and automatically tag content within the taxonomy. 

Using Natural Language Processing (NLP) engines and large language models, media organizations can automatically and dynamically classify and categorize content, without the need for predefined taxonomies. NLP engines understand and expertly tag content, creating a dynamic set of semantic understanding. This automated tagging can be used to auto-generate a taxonomy or complement a structured taxonomy with additional insights.

Hum’s Alchemist Taxonomy & Tagging Engine learns from your full, growing library of content through several sophisticated layers of interpretive and generative AI - extracting key terms, understanding context, and constructing a custom taxonomy.

The use of AI-generated taxonomies provides several immediate benefits for media organizations, including:

  • Increased Efficiency: AI can automatically generate and update taxonomies based on evolving content and news trends, streamlining content management and reducing the time required to create and maintain taxonomies.
  • Consistency in Categorization and Tagging: AI systems learn from the content, developing a better understanding of relationships between different pieces of content, leading to more accurate and consistent tagging.
  • Improved Scalability: As new content is created, AI systems can automatically analyze and categorize it. Ensuring the taxonomy remains up-to-date and relevant is particularly beneficial for media organizations dealing with large volumes of content.
  • Flexibility: Unlike traditional taxonomies, AI-generated taxonomies can be easily updated and customized to suit the unique requirements of a media organization and its rapidly changing content landscape.

AI-generated taxonomies get better results

AI-generated taxonomies can help media organizations find information, group related content, and compare ideas across various news stories and content pieces. AI's deep understanding of content goes beyond one-dimensional tags, allowing for more efficient and effective categorization and search.

Media organizations are using the Alchemist Taxonomy & Tagging Engine to:

  • Create custom collections of content based on topics, keywords, or engagement.
  • Build and develop segments based on direct subject engagement or predictive interests. 
  • Identify emerging topics and news, and match it with the perfect audience in seconds

As AI continues to advance, media organizations should consider the benefits of AI-generated taxonomies and plan to integrate them into their operations. 

By embracing AI-powered content organization, media organizations can stay ahead of the curve, improving their ability to manage, categorize, and deliver content in an increasingly complex and rapidly evolving digital landscape.