Hum’s AI Taxonomy Tool
Unlock your content's full potential.
CueBERT uses artificial intelligence (AI) and natural language processing (NLP) to automatically and consistently apply topic tags to content in real-time, so you can get more value from your content library.
Identify Trends &
Get a more accurate measure of your content inventory. CueBERT constantly ingests reader behavior to deliver predictive analytics in real-time, including: trending topic combinations, underperforming content themes, and top keyword opportunities across your full library.
HOW DOES IT WORK?
Hum’s Content Tagging Engine
CueBERT, Hum’s content tagging engine, reads a piece of content: Journal articles, books, webpages, videos, blogs, and more.
Anything connected to Hum.
CueBERT applies 5-7 keywords per content item. CueBERT can be trained on existing taxonomies as well, applying those terms in addition.
CueBERT listens for new content to be published and automatically applies keywords to that new content.
Get a more accurate measure of your content inventory. CueBERT constantly ingests reader behavior to deliver trending topic combinations, underperforming content themes, and top keyword opportunities across your full library.
Take advantage of opportunities to increase programmatic ad yield. CueBERT uncovers patterns in the topics readers are most interested in and allows you to serve more effective, more targeted ads.
Find the content your readers care about and filter out the noise. Improved tagging gives Hum the power to predict what readers want to see next, so you can personalize marketing and content recommendations based on readers’ specific interests.
Tagged content is searchable content. CueBERT helps classify and categorize your content, so you can optimize existing content and drive SEO value so the right new readers can discover it.