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Knowledge Graph Embeddings

23 papers with code · Graphs

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Convolutional 2D Knowledge Graph Embeddings

5 Jul 2017TimDettmers/ConvE

In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

NAACL 2018 cai-lw/KBGAN

This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.

KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

ACL 2019 deepakn97/relationPrediction

The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction).

KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs

7 Sep 2017nle-ml/mmkb

A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.

IMAGE RETRIEVAL KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS ZERO-SHOT LEARNING

Recommendation Through Mixtures of Heterogeneous Item Relationships

29 Aug 2018kang205/MoHR

Recommender Systems have proliferated as general-purpose approaches to model a wide variety of consumer interaction data.

KNOWLEDGE GRAPH EMBEDDINGS RECOMMENDATION SYSTEMS

Quaternion Knowledge Graph Embeddings

NeurIPS 2019 cheungdaven/QuatE

In this work, we move beyond the traditional complex-valued representations, introducing more expressive hypercomplex representations to model entities and relations for knowledge graph embeddings.

KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION

Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text

4 Jul 2018YueLiu/NeuralTripleTranslation

Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.

KNOWLEDGE GRAPH EMBEDDINGS