Graph Database Recommendation Engine

Recommendation Engine performed a role that connects people to products, services, and information through analysis among their relationship, offer optimal result at the rapid time. Key point for its task is to offer faster and real-time recommendation to people what people want by system. So companies get more profit. Recommendation Engine is a kind of graph data important definition and analysis social connections or connecting the dots between seemingly unrelated facts to infer interests. And the strength is faster and computable through available process directly.

Graph databases have revolutionized the way people discover new products, services, information and people. Recommendation engines powered by graph databases help companies to personalize products, contents and services by leveraging the connections between data — all in real time and connect people to products, services, information or other people based on user profile, preferences and past online activity such as product purchases. Graph databases also enable users to search for products, services or people based on a host of fine-grained criteria and continually improve recommendations by accommodating new data sources and types.

A simple way is each product assuming that a Node, when customer bought product2 who also bought product1, make relationship among product1 to product2 with improve weight. Afterward, graph database can be used when some people want to buy same product, the way offer real-time recommend heavy weight’s product top 5 related to this product in graph database.