Practice English vocabulary for knowledge graph business applications: entity-aware search, fraud detection, recommendation engines, and identity graphs.
0 / 5 completed
1 / 5
What does 'the knowledge graph powers entity-aware search' mean?
Entity-aware search maps query terms to graph entities and expands results using graph relationships. Searching for 'Apple products under $500' resolves 'Apple' to the company entity and traverses its product relationships, filtering by price — impossible with simple keyword search.
2 / 5
What does 'the fraud detection graph connects suspicious entities' mean?
Graph-based fraud detection excels at finding connected fraud: multiple accounts sharing a device, a network of accounts linked by the same IP, or synthetic identity rings. Graph traversal reveals these connections that row-based ML models miss.
3 / 5
What does 'the recommendation engine uses the product knowledge graph' mean?
Knowledge graph recommendations use semantic relationships to suggest items: 'users who bought this vitamin also bought these related supplements' or 'this recipe uses ingredients you already bought'. The graph's rich entity relationships enable explainable, context-aware recommendations.
4 / 5
What is 'the customer 360 view built on the identity graph'?
Identity resolution links fragmented customer data (mobile app user, web visitor, email subscriber, in-store loyalty member) into a unified identity. Built on a graph, the customer 360 view allows personalization, support, and analytics that see the complete customer relationship.
5 / 5
How does a team 'justify investment in a knowledge graph' to business stakeholders?
Knowledge graph ROI is communicated in business terms. Technical complexity only earns investment if paired with measurable outcomes: 'our knowledge graph reduced fraud losses by $2M', 'search conversion improved 15%', or 'analyst time for cross-domain queries reduced from 3 days to 10 minutes'.