Asan Agibetov | DeepAI

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Featured Co-authors

Jiaoyan Chen
46 publications
Matthias Samwald
28 publications
Ernesto Jiménez-Ruiz
18 publications
Simon Ott
8 publications
Christian Meilicke
7 publications
Anna Breit
4 publications
Valerie Cross
2 publications
Laura Graf
1 publication

∙ 12/10/2020

Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs

Neural embedding-based machine learning models have shown promise for pr...

0 Simon Ott, et al. ∙

∙ 11/16/2020

Graph embeddings via matrix factorization for link prediction: smoothing or truncating negatives?

Link prediction – the process of uncovering missing links in a complex n...

0 Asan Agibetov, et al. ∙

∙ 05/15/2020

Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes

Recently, link prediction algorithms based on neural embeddings have gai...

0 Asan Agibetov, et al. ∙

∙ 02/25/2020

Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules

Large ontologies still pose serious challenges to state-of-the-art ontol...

0 Ernesto Jiménez-Ruiz, et al. ∙

∙ 12/10/2019

OpenBioLink: A benchmarking framework for large-scale biomedical link prediction

SUMMARY: Recently, novel machine-learning algorithms have shown potentia...

0 Anna Breit, et al. ∙

∙ 12/10/2019

OpenBioLink: A resource and benchmarking framework for large-scale biomedical link prediction

SUMMARY: Recently, novel machine-learning algorithms have shown potentia...

0 Anna Breit, et al. ∙

∙ 07/27/2018

Global and local evaluation of link prediction tasks with neural embeddings

We focus our attention on the link prediction problem for knowledge grap...

0 Asan Agibetov, et al. ∙

∙ 05/31/2018

Breaking-down the Ontology Alignment Task with a Lexical Index and Neural Embeddings

Large ontologies still pose serious challenges to state-of-the-art ontol...

0 Ernesto Jiménez-Ruiz, et al. ∙

∙ 04/30/2018

Fast and scalable learning of neuro-symbolic representations of biomedical knowledge

In this work we address the problem of fast and scalable learning of neu...

0 Asan Agibetov, et al. ∙

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