Ontologies and knowledge graphs are important in informatics, but they have not yet been developed in exercise medicine. In this chapter, I first explain what an ontology is, what a knowledge graph is, and what their relationship is. Then I focus on ontology by introducing related research and...
O=Ontology-based / 本体依赖: Knowledge graphs often rely on ontologies or schemas to define the types of entities, relationships, and properties that can be represented in the graph. 知识图谱经常依赖于本体或模式定义图形中可以表示的实体类型、关系和属性。 W=Wide Range of Data Sources / 多元数据...
When learning about knowledge graphs, you might come across articles onontologiesand wonder where they fit in. An ontology is a formal specification of the concepts and the relationships between them for a given subject area; semantic networks are a common way to represent ontologies. Put simply,...
modelingsystems-biologyepidemiologydifferential-equationsontologiesmodeling-and-simulationknowledge-graphs UpdatedFeb 28, 2025 Jupyter Notebook greenelab/knowledge-graph-review Star11 Code Issues Pull requests A literature review for constructing and using knowledge graphs in a biomedical setting. ...
First things first. There are two types of main graph data models: Property Graphs and Knowledge (RDF) Graphs.The property graph data modelgenerally comprises three elements: Nodes: The entities in the graph. Edges: The directed links between nodes. Consider them relationships. ...
Niels demonstrates how to use NeoDash and OpenAI to create Neo4j LLM dashboards with natural language. Using a brand new plugin, you can visualize Neo4j data in tables, graphs, maps, and more – without writing any Cypher! 4. Cyberattack Countermeasures Generation With LLMs & Knowledge Graphs...
The integration of such inheritances and interconnections is what makes bi-directional knowledge graphs more powerful than simple trees and other radial maps when it comes to capturing dynamic knowledge—which is why they can be used to capture complex thought processes as well. ...
The article first provides an overview of the definitions of knowledge reasoning in different academic periods, from early deductive reasoning methods based on logicism to the current data-driven machine reasoning methods. Then, it introduces some leading knowledge graphs. ...
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering ...
medical knowledge graphs, such as DistMult, RotatE, ConvE, InteractE, JointE, and ConvKB, may not adequately capture the unique challenges posed by the domain, including the heterogeneity of medical entities, rich hierarchical structures, large-scale, high-dimensionality, and noisy and incomplete data...