Content Recommendation
Get user-focused recommendations that personalize the user experience by delivering contextual content. Ontotext’s Content Recommendation provides suggestions for relevant content based on natural language processing, search history, user profiles and semantically enriched data.
Key Features:
- Personalized recommendations
- Contextual recommendations
- Scalable & efficient
How you’ll benefit
Increase the engagement of your users
Provide your authors with the ability to find relevant content
Generate personalized content streams
How it works
Content suggestions
By leveraging the documents’ semantic fingerprints extracted by the Concept Extraction Service, The Recommendation Service efficiently suggests relevant related content.
Behavioral recommendations
The quality of the Recommendation Service is further enhanced by custom tailored behavioral recommendations, based on the actions of the readers and their profiles.
Standard Solution vs Custom Solution
| Solutions Comparison | Standard Solution | Custom Solution |
|---|---|---|
| Contextual Recommendation | ||
| Behavioural Recommendation | ||
| Hybrid Algorithms | ||
| Out of the Box Semantic Tagging | ||
| Integration with Click/Content Stream | ||
| Installation and Training | ||
| Support | ||
| Optional customization of the Semantic Tagging for your domain |
