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Knowledge Graphs

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A Neural Architecture for Person Ontology population

22 Jan 2020

A person ontology comprising concepts, attributes and relationships of people has a number of applications in data protection, didentification, population of knowledge graphs for business intelligence and fraud prevention.

KNOWLEDGE GRAPHS RELATION EXTRACTION

Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs

9 Jan 2020

The underlying idea is to frame the task of triple classification as a debate game between two reinforcement learning agents which extract arguments -- paths in the knowledge graph -- with the goal to justify the fact being true (thesis) or the fact being false (antithesis), respectively.

COMMON SENSE REASONING KNOWLEDGE GRAPHS

Knowledge Graphs for Innovation Ecosystems

9 Jan 2020

An ontology to capture the essential entities and relations is presented, as well as the description of data sources, which can be used to populate innovation knowledge graphs.

KNOWLEDGE GRAPHS

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

8 Jan 2020

Large-scale knowledge graphs (KGs) are shown to become more important in current information systems.

KNOWLEDGE GRAPH COMPLETION RELATIONAL REASONING ZERO-SHOT LEARNING

Bridging Knowledge Graphs to Generate Scene Graphs

7 Jan 2020

Based on this new perspective, we re-formulate scene graph generation as the inference of a bridge between the scene and commonsense graphs, where each entity or predicate instance in the scene graph has to be linked to its corresponding entity or predicate class in the commonsense graph.

GRAPH GENERATION KNOWLEDGE GRAPHS SCENE GRAPH GENERATION

Quantum Machine Learning Algorithm for Knowledge Graphs

4 Jan 2020

We simplify the problem by making a plausible assumption that the tensor representation of a knowledge graph can be approximated by its low-rank tensor singular value decomposition, which is verified by our experiments.

KNOWLEDGE GRAPHS QUANTUM MACHINE LEARNING

Differentiable learning of numerical rules in knowledge graphs

ICLR 2020

Rules over a knowledge graph (KG) capture interpretable patterns in data and can be used for KG cleaning and completion.

KNOWLEDGE GRAPHS

TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces

ICLR 2020

TransINT maps set of entities (tied by a relation) to continuous sets of vectors that are inclusion-ordered isomorphically to relation implications.

KNOWLEDGE GRAPHS LINK PREDICTION

Toward Understanding The Effect of Loss Function on The Performance of Knowledge Graph Embedding

ICLR 2020

We show that by a proper selection of the loss function for training the TransE model, the main limitations of the model are mitigated.

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS