Graph Technology in Recommendation Engines
Having a truly accurate and adaptable recommendation engine can either make or break a business, and keeping up with the rapid growth and complexity of data is not an easy task. Luckily, graph databases and algorithms specifically designed to analyze customer behavior provide powerful and real-time recommendations.
With this whitepaper, you will find out that:
- Data is easier to model and query using graph technology
- Graph data models effortlessly adapt and keep up with the market demands
- Graph algorithms are the key to creating valuable recommendations
- Memgraph’s in-memory and C++ architecture can considerably speed up your system
- Memgraph supports real-time analytics, thus making predictions and correcting errors within seconds