The development of a reliable recommender engine requires a structured and consistent content and data management. PoolParty equips you with all necessary tools and algorithms to enable your customers to benefit from a first-class user experience thanks to the precise personalization of content.
The Realities of Online Personalization
PoolParty’s Answer to the Challenge:
- Build a PoolParty knowledge graph that classifies your content subjects.
- Link subject categories with each other and start developing a content network.
- Use the PoolParty module ‘Entity Extractor’ to analyze your content and match it with your knowledge graph.
- Metadata gets automatically attached to your content repository. You can manually adapt it if necessary.
- The semantic information embodied in the knowledge graph and the content itself is what makes content recommendation work.
- PoolParty’s Content Recommender lets you build a sustainable framework for delivering automatically existing information to various stakeholders.
- Your context-based content gets frequently reused.
- You generate new ‘digital products’ through topic pages that are created and automatically updated by the Content Recommender.
Take a Closer Look at the Content Recommender:
PoolParty Modules at a Glance
How to Build a Recommender
How to Build a Recommender System:
Read the Use Case!