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Structure embedding for knowledge base completion and analytics
Zili ZHOU
,
Guandong XU
, Wenhao ZHU
, Jinyan LI
, Wu ZHANG
Offices of the President (P)
Research output
:
Chapter in Book/Report/Conference proceeding
›
Chapters
2
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Citations (Scopus)
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Dive into the research topics of 'Structure embedding for knowledge base completion and analytics'. Together they form a unique fingerprint.
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Keyphrases
Knowledge Base
100%
Knowledge Base Completion
100%
Structure Embedding
100%
Bipartite Graph Network
100%
Embedding Method
66%
Triplet
44%
Multiple Relationships
33%
Multiple Entities
33%
Basis Elements
33%
Previous Knowledge
22%
Vector Space Representation
22%
Entity Relation
22%
Embedding Framework
22%
Copyright
11%
Knowledge Embedding
11%
Training Data
11%
Network Model
11%
Human Knowledge
11%
Collaborative Filtering
11%
WordNet
11%
Structure Analysis
11%
Bipartite Graph
11%
Link Weight
11%
True or False
11%
Embedding Representation
11%
Base-free
11%
Weight Matrix
11%
Network Layer
11%
Knowledge Reasoning
11%
Embedding Model
11%
Model Use
11%
Relation Embedding
11%
Backward Propagation
11%
TransE
11%
Entity Embedding
11%
Linear Vectors
11%
Bipartite Graph Model
11%
Nonlinear Networks
11%
Forward Propagation
11%
Structure Completion
11%
Entity Knowledge
11%
Low-dimensional Vectors
11%
Subspace Projection
11%
Proper Embedding
11%
Vector Transform
11%
Latent Information
11%
Image Data Compression
11%
Network Structure Model
11%
Computer Science
Knowledge Base
100%
Bipartite Graph
91%
Embedding Method
50%
Space Representation
16%
Network Structures
8%
Training Data
8%
Human Knowledge
8%
Structure Model
8%
Collaborative Filtering
8%
Data Compression
8%
Network Layer
8%
Dimensional Vector Space
8%
Subspace Projection
8%