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> ML_ALGORITHM // ROTATE-COMPLEX-SPACE-RELATIONAL-EMBEDDING_v1.0

RotatE (Knowledge Graph Embedding by Relational Rotation)

Knowledge graph embedding framework defining relations as element-wise rotations in complex vector space, theoretically unifying major relational patterns.

Knowledge Graph Embeddingsgraph-relationalhigh-intrinsiclarge (>100k)
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Computational Complexity
Training Complexity:O(triplets * d_complex * epochs)
Inference Complexity:O(d_complex)
Hardware Profile
CPU Friendly:Yes
Requires GPU:Yes
Memory Footprint:low
Interpretability & Data
Interpretability Tier:high-intrinsic
Training Data Needs:large (>100k)

Interpretability Assessment

Rotational angles in the complex plane directly capture algebraic relational patterns without parameter bloat.

Suitable Tasks & Supported Modalities

Suitable Tasks:
knowledge graph completionlink prediction
Supported Modalities:
graph

Implementing Libraries

pykeen
dgl-ke

Foundational Literature

Common Pitfalls & Warnings
  • Complex embeddings must be constrained to unit modulus; unconstrained norms break rotation algebra