Quaternion Knowledge Graph Embeddings

[1904.10281] Quaternion Knowledge Graph Embeddings - arXiv

Quaternion embeddings, hypercomplex-valued embeddings with three imaginary components, are utilized to represent entities. Relations are modelled as rotations.

More concretely, quaternion embeddings are utilized to represent entities and relations. Each quaternion embedding is a vector in the hypercomplex space H with ...

Quaternion knowledge graph embeddings - ACM Digital Library

More specifically, quaternion embeddings, hypercomplex-valued embeddings with three imaginary components, are utilized to represent entities. Relations are ...

Quaternion Knowledge Graph Embeddings (2019) - Hacker News

All euclidean embeddings have a minimum error of 20-40% or so. If you try to embed any graph containing that subgraph (embedding friends, advertisers, words, ..

Pytorch implementation of Quaternion Knowledge Graph Embeddings.

Pytorch implementation of Quaternion Knowledge Graph Embeddings. - cheungdaven/QuatE.

Reviews: Quaternion Knowledge Graph Embeddings

This paper proposes a knowledge graph embedding model where entities and relations are represented in the quaternion space - this generalises some recent ...

Learning Hierarchy-Aware Quaternion Knowledge Graph ...

The relational embedding consists of two parts: (a) Using unit quaternions to represent the rotation part in 3D space, where the head entities are rotated by ...

Dual Quaternion Knowledge Graph Embeddings

We propose a new method called dual quaternion knowledge graph embedding (DualE), which introduces dual quaternions into knowledge graph embeddings.

Learning Hierarchy-Aware Quaternion Knowledge Graph ...

Knowledge graph embedding aims to represent entities and relations as low-dimensional vectors, which is an effective way for predicting missing links.

[PDF] Quaternion Knowledge Graph Embeddings - Semantic Scholar

This work moves beyond the traditional complex-valued representations, introducing more expressive hypercomplex representations to model entities and ...

Relation-Aware Quaternions for Knowledge Graph Embeddings

Abstract. We propose a simple yet effective embedding model to learn quaternion embeddings for entities and relations in knowledge graphs. Our model aims to ...

Quaternion Knowledge Graph Embeddings - arXiv

Quaternion Embeddings of Knowledge Graphs More specifically, we use a quaternion matrix. Q ∈ HN×k to denote the entity embeddings and W ∈ HM×k ...

Dual Quaternion Knowledge Graph Embeddings - AAAI

To embrace a richer set of relational information, we propose a new method called dual quaternion knowledge graph embeddings (DualE), which introduces dual.

Quaternion Knowledge Graph Embedding - Semantic Scholar

This paper moves beyond standard complex representations, adopting expressive hypercomplex representations for learning representations of entities and ...

Knowledge Graph Embedding with Relation Rotation and Entity ...

Recent knowledge graph embedding models have shown promising results on link prediction, by employing operations on quaternion space to ...

Relation-Aware Quaternions for Knowledge Graph Embeddings

We propose an effective embedding model, named QuatRE, to learn quaternion embeddings for entities and relations in knowledge graphs.

Quaternion Knowledge Graph Embeddings. - DBLP

Bibliographic details on Quaternion Knowledge Graph Embeddings.

Knowledge graph completion method based on quantum ...

In this study, we propose a new KGC method referred to as QIQE-KGC. It uses quantum embedding and quaternion space interaction to capture the external logical ...

Dynamic dual quaternion knowledge graph embedding - SpringerLink

This paper proposes a novel knowledge graph embedding model called DualDE, which dynamically maps the dual quaternions to the knowledge graph.

Dual Quaternion Knowledge Graph Embeddings | Request PDF

DualE [4] introduces dual quaternions into knowledge graph embeddings, providing a unified framework for modeling both rotation and translation operations in 3D ...