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Knowledge Graphs

122 papers with code · Knowledge Base

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A Physical Embedding Model for Knowledge Graphs

21 Jan 2020dice-group/PYKE

We present a novel and scalable paradigm for the computation of knowledge graph embeddings, which we dub PYKE .

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS

1
21 Jan 2020

Reasoning on Knowledge Graphs with Debate Dynamics

2 Jan 2020m-hildebrandt/R2D2

The main 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 promote the fact being true (thesis) or the fact being false (antithesis), respectively.

KNOWLEDGE GRAPHS LINK PREDICTION

2
02 Jan 2020

FALCON 2.0: An Entity and Relation Linking Tool over Wikidata

24 Dec 2019SDM-TIB/Falcon2.0

The input of Falcon 2. 0 is a short natural language text in the English language.

KNOWLEDGE GRAPHS

16
24 Dec 2019

Knowledge-Enriched Visual Storytelling

3 Dec 2019zychen423/KE-VIST

This paper introduces KG-Story, a three-stage framework that allows the story generation model to take advantage of external Knowledge Graphs to produce interesting stories.

KNOWLEDGE GRAPHS VISUAL STORYTELLING

10
03 Dec 2019

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

21 Nov 2019MIRALab-USTC/KGE-HAKE

HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

17
21 Nov 2019

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation

20 Nov 2019nju-websoft/AliNet

As the direct neighbors of counterpart entities are usually dissimilar due to the schema heterogeneity, AliNet introduces distant neighbors to expand the overlap between their neighborhood structures.

ENTITY ALIGNMENT KNOWLEDGE GRAPHS

11
20 Nov 2019

Rule-Guided Compositional Representation Learning on Knowledge Graphs

20 Nov 2019ngl567/RPJE

Representation learning on a knowledge graph (KG) is to embed entities and relations of a KG into low-dimensional continuous vector spaces.

KNOWLEDGE GRAPHS REPRESENTATION LEARNING

4
20 Nov 2019

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned

19 Nov 2019Valentyn1997/kg-alignment-lessons-learned

In this work, we focus on the problem of entity alignment in Knowledge Graphs (KG) and we report on our experiences when applying a Graph Convolutional Network (GCN) based model for this task.

ENTITY ALIGNMENT KNOWLEDGE GRAPHS

2
19 Nov 2019

Decompressing Knowledge Graph Representations for Link Prediction

11 Nov 2019shawnkx/Decom

Specifically, embeddings of entities and relationships are first decompressed to a more expressive and robust space by decompressing functions, then knowledge graph embedding models are trained in this new feature space.

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS LINK PREDICTION

5
11 Nov 2019

Relation Adversarial Network for Low Resource Knowledge Graph Completion

8 Nov 2019zxlzr/RAN

Specifically, the framework takes advantage of a relation discriminator to distinguish between samples from different relations, and help learn relation-invariant features more transferable from source relations to target relations.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION PARTIAL DOMAIN ADAPTATION RELATION EXTRACTION

1
08 Nov 2019