- Engagement engine – mine usage patterns to understand users’ evolving interaction preferences in order to identify optimal times and channels to engage with users
- Recommendations engine – create personalized learning recommendations leveraging user-content interactions, content ontologies and temporal consumption patterns
- Visualization techniques – to provide visual context for the recommendations to explain to the user why certain personalized content recommendations are being made along three different dimensions: people similar to the user liked this content, content similar to content the user liked, and popular content
Skillsoft And IBM Reveal New Capabilities For Big Data In Enterprise Learning
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