📌 Graph Knowledge Modeling Summary
Graph knowledge modelling is a way to organise and represent information using nodes and relationships, much like a map of connected points. Each node stands for an item or concept, and the links show how these items are related. This approach helps computers and people understand complex connections within data, making it easier to search, analyse, and visualise information.
🙋🏻♂️ Explain Graph Knowledge Modeling Simply
Imagine a spider web where each knot is a piece of information, and the threads connecting them show how they relate. This makes it simple to trace paths from one idea to another, just like following links between friends on a social network.
📅 How Can it be used?
Use graph knowledge modelling to map relationships between products, suppliers, and customers for better supply chain management.
🗺️ Real World Examples
A medical research team uses graph knowledge modelling to connect diseases, symptoms, treatments, and patient data. This helps them spot patterns, such as which treatments are most effective for patients with specific symptom clusters, and supports faster, more accurate diagnosis.
A publishing company applies graph knowledge modelling to link authors, books, genres, and publication dates. This allows them to recommend new books to readers based on shared themes or author collaborations, improving their recommendation system.
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