Training a GNN by querying a graph database for neighbor samples and features reduces memory use enough to train on small machines, but is much slower than in-memory training.
Formal Semantics of the Language Cypher
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abstract
Cypher is a query language for property graphs. It was originally designed and implemented as part of the Neo4j graph database, and it is currently used in a growing number of commercial systems, industrial applications and research projects. In this work, we provide denotational semantics of the core fragment of the read-only part of Cypher, which features in particular pattern matching, filtering, and most relational operations on tables.
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Graph Neural Networks on Graph Databases
Training a GNN by querying a graph database for neighbor samples and features reduces memory use enough to train on small machines, but is much slower than in-memory training.