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Extracting valuable hidden knowledge from large-scale data relies on Reasoning Technology support. Knowledge Graphs, as a new type of knowledge representation, have received much attention in Knowledge Modeling. Knowledge graphs can effectively organize and represent knowledge so that it can be used effectively in advanced applications.

Reasoning on Knowledge graphs has recently become a hot topic of research because it can produce new knowledge and conclusions from existing data.

Reasoning methods are classified into three categories:

1- Rule-Based Reasoning

2- Distributed representation-based reasoning

3- Neural Network-based reasoning.

In the Borhan team, we use different methods of reasoning to develop and validate the knowledge graph.

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