Heterogeneous graph

As explained in Graph Algorithms for Data Science

A heterogeneous graph contains multiple node types or multiple relationship types.

A heterogeneous graph contains multiple node types or relationship types. Unlike a homogeneous graph, it preserves distinctions between entities and connections, making it suitable for knowledge graph completion and other typed-link prediction tasks. section 11.0 section 11.4

Key modeling characteristics include:

• Represent directed facts as triples containing a head entity, relation, and tail entity. section 11.4
• Allow several relationship types between the same entity types and distinguish those types during prediction. section 11.0 section 11.4
• Support knowledge graph embeddings that encode both nodes and relationships rather than nodes alone. section 11.4

Drug repurposing

A biomedical graph can connect existing drugs with known treatments and represent additional entity and relationship types. Knowledge graph completion then predicts missing drug–treatment links, which domain experts evaluate before clinical trials. The predictions prioritize candidates rather than approving new uses automatically. section 11.0 section 11.4

Figure 11.4 Example schema of a complex biomedical graph

Use the complex biomedical graph schema to inspect how multiple entity and relationship types can coexist in one graph. section 11.0

How Graph Algorithms for Data Science covers it

How deep it goes

Defines node, relationship, and triple types, then connects them to embedding models and multiclass link prediction.

Examples

Uses stream-sharing graphs, drug-treatment networks, and a complex biomedical graph schema as contrasting examples.

What you can do after

Evaluate typed-link predictions as candidates for expert review and subsequent clinical trials.

How it connects

Connects homogeneous graphs, link prediction, knowledge graph embeddings, knowledge graph completion, and drug repurposing.

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Also explained in

• 

  liveBookmanning.com
  Knowledge Graphs and LLMs in ActionA heterogeneous graph is a graph containing multiple types of nodes, relationships, or both.
• 

  liveBookmanning.com
  Graph Neural Networks in ActionA heterogeneous graph is a graph containing multiple types of nodes or edges.

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Related concepts

• homogeneous graphcontrasts with · A homogeneous graph is a graph whose nodes share one type and whose edges or relationships share one type.
• knowledge graphincludes · A knowledge graph is a graph-structured representation of entities and their semantically meaningful relationships, often including associated attributes or facts.
• graphkind of · A graph is a mathematical structure consisting of vertices connected by edges that represent relationships or connections.
• knowledge graph embeddingaddressed by · Knowledge graph embedding is a technique that represents entities and relationships as low-dimensional vectors while preserving patterns expressed by valid triples.

This explainer was generated by Manning's knowledge graph from the text of Graph Algorithms for Data Science. The section links point to the parts of the book it draws on.