What does "Class Granularity" mean?
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Class Granularity is a way to measure how detailed and specific categories are in a knowledge graph. It looks at how well different classes with unique traits are defined. The more specific the classes, the better the overall structure of the knowledge graph.
Importance of Class Granularity
Understanding Class Granularity is important because it can influence various tasks that use knowledge graphs. For example, when working with data in the graph, having well-defined classes can lead to better results in things like graph embedding, which helps in representing the information in a useful way.
Comparing Different Data Sources
Class Granularity can also help compare different data sources. Instead of just looking at how much data is in each source or how classes are spread out, this metric focuses on how well the classes are defined. This can give a clearer picture of the quality of the data and how it can be used effectively.