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Recommendation systems have advanced in recent years, but organizations still grapple with heterogeneous, sparse or insufficient data, as well as problems such as repeated patterns (echo chamber effect). These issues can cause bottlenecks for generating highly-personalized recommendations. At the individual level, personalized recommendations are becoming increasingly relevant to businesses with a large product portfolio and customer base. They are essential for businesses to improve customer satisfaction, resulting in increased revenues, expanded product portfolios, and loyal customers. In this talk we will review the importance of:
- Building a knowledge graph using labeled property graph technology
- Capturing the evolution of user interactions with the business
- Using knowledge graphs and graph data science to build context-aware recommendation systems
Don't miss this live event on Tuesday, March 7, 11am PT / 2pm ET.
Register now to attend Solving Data Challenges with Knowledge Graphs and Context-Aware Recommendation Systems.
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