Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs
From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction
Knowledge Representation Learning with Entities, Attributes and Relations
Sparse Word Embeddings Using L1 Regularized Online Learning
Bag-of-Embeddings for Text Classification
Exploring the Context of Locations for Personalized Location Recommendations
Text-enhanced Representation Learning for Knowledge Graph
Representation Learning of Knowledge Graphs with Hierarchical Types
Querying Data Graphs with Arithmetical Regular Expressions
Learning First-Order Logic Embeddings via Graph Rewriting
Predict Anchor Links across Social Networks via an Embedding Approach
Aligning Users Across Social Networks Using Network Embedding
Grounding Topic Models with Knowledge Bases
KOGNAC: Efficient Encoding of Large Knowledge Graphs
Max-Margin DeepWalk: Discriminative Learning of Network Representation