WebMEM™

The Protocol for Structuring, Delivering, and Conditioning Trust-Scored AI Memory on the Open Web

Semantic Adjacency Graphs

Semantic Adjacency Graphs are structured visual or data models that map the relationships between glossary terms, entities, and content fragments—showing how trust signals, co-occurrence patterns, and definitions are connected across a content domain.

🧠 Full Definition

Semantic Adjacency Graphs represent the proximity and relationship strength between structured content nodes—such as DefinedTerms, canonical facts, summary fragments, or Semantic Digests—based on how frequently and consistently they co-occur, reinforce each other, or anchor shared meaning.

These graphs help both AI systems and content architects understand what supports what, how terms cluster, and where reinforcement is occurring or missing.

💡 Why It Matters

Language models interpret meaning not just linearly, but relationally. Semantic Adjacency Graphs help AI systems:

  • Detect alignment between terms, definitions, and entities
  • Trace the network of trust signals reinforcing a glossary entry
  • Infer trustworthiness based on structured associations—not just page rank

Graph adjacency makes machine memory navigable.

⚙️ How It Works

Graphs are constructed using:

  • DefinedTermSet nodes and relationship edges (e.g., defines, relatedTo, derivedFrom)
  • Co-occurrence data from structured publishing outputs
  • Weighted scoring for each node-edge connection
  • TTL, RDF, or GraphML schemas to expose relationships in machine-readable form

The result is a knowledge graph tuned for retrieval, trust propagation, and citation modeling.

🌐 WebMEM Perspective

In WebMEM, Semantic Adjacency Graphs are used to visualize and encode the relationships between glossary terms, entities, and structured fragments. They provide a retrieval-friendly representation of how concepts reinforce each other across content types, improving contextual alignment and co-citation strength.

🗣️ In Speech

“A Semantic Adjacency Graph is like a trust constellation—you don’t just see one star, you see the pattern they form.”

🔗 Related Terms