In the previous example, we focused on a core data catalog ontology ... of the flexibility of the graph model and its ability to power questions. The knowledge-graph data model is by definition ...

For example, a user might input a question like “Which policies have a high-risk rating?” and the LLM can generate a Cypher query to extract the relevant data from the graph. The knowledge ...

Knowledge graphs can provide a solution, effectively modeling organizational hierarchies, user roles and access permissions. Developed to handle large amounts of interconnected data, they ...

Knowledge graphs are reshaping ... represent individual data points – such as a client, a tool they use or a marketing goal they have. For example, imagine three nodes: “Client A ...

They also are employed to construct knowledge graphs that ... grid-like datasets. For example, relational is ideally suited to the management of financial transactions or product inventories.” At the ...

Signals are converging and leading me to believe that 2025 is the Year of the Knowledge Graph. But before we get carried away ...

Therefore, we have focused our work on integrating data ... knowledge graph with the same information we used for the RAG. Is the quality of the answers better? Let’s see on the same example.

It structures data in a meaningful way, enabling greater efficiencies and accuracies in retrieving information. LinkedIn, for example, uses a knowledge graph to structure and interconnect data ...

The model for the Dimensions Knowledge Graph was built using metaphactory’s semantic modeling interface, which is based on open standards and supports data reusability across all use cases and ...