Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs

Research output: Contribution to ConferencePosterAcademic

Abstract

Recent years have seen the emergence of graph-based Knowledge Bases build upon
Semantic Web technologies, known as Knowledge Graphs. Effectively learning from
these complex relational structures remains a challenge yet to be overcome.
Knowledge Graphs For this purpose, we are investigating the effectiveness of Link Prediction through
means of Deep Learning an Artificial Neural Network, as well to optimize both
learning method and model through Bayesian Hyper-parameter optimization.
Moreover, during evaluation, special attention will be given to the usefulness of made

Conference

ConferenceECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Abbreviated titleECML
CountryPortugal
CityPorto
Period7/09/1511/09/15
Internet address

Fingerprint

Semantic Web
Neural networks
Deep learning
Deep neural networks

Keywords

  • Knowledge Graphs
  • Deep Learning

Cite this

Wilcke, W. X. (2015). Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs. Poster session presented at ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal.
Wilcke, W.X. / Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs. Poster session presented at ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal.
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title = "Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs",
abstract = "Recent years have seen the emergence of graph-based Knowledge Bases build upon Semantic Web technologies, known as Knowledge Graphs. Effectively learning from these complex relational structures remains a challenge yet to be overcome.Knowledge Graphs For this purpose, we are investigating the effectiveness of Link Prediction through means of Deep Learning an Artificial Neural Network, as well to optimize both learning method and model through Bayesian Hyper-parameter optimization. Moreover, during evaluation, special attention will be given to the usefulness of made",
keywords = "Knowledge Graphs, Deep Learning",
author = "W.X. Wilcke",
year = "2015",
language = "English",
note = "ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML ; Conference date: 07-09-2015 Through 11-09-2015",
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}

Wilcke, WX 2015, 'Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs' ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, 7/09/15 - 11/09/15, .

Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs. / Wilcke, W.X.

2015. Poster session presented at ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal.

Research output: Contribution to ConferencePosterAcademic

TY - CONF

T1 - Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs

AU - Wilcke, W.X.

PY - 2015

Y1 - 2015

N2 - Recent years have seen the emergence of graph-based Knowledge Bases build upon Semantic Web technologies, known as Knowledge Graphs. Effectively learning from these complex relational structures remains a challenge yet to be overcome.Knowledge Graphs For this purpose, we are investigating the effectiveness of Link Prediction through means of Deep Learning an Artificial Neural Network, as well to optimize both learning method and model through Bayesian Hyper-parameter optimization. Moreover, during evaluation, special attention will be given to the usefulness of made

AB - Recent years have seen the emergence of graph-based Knowledge Bases build upon Semantic Web technologies, known as Knowledge Graphs. Effectively learning from these complex relational structures remains a challenge yet to be overcome.Knowledge Graphs For this purpose, we are investigating the effectiveness of Link Prediction through means of Deep Learning an Artificial Neural Network, as well to optimize both learning method and model through Bayesian Hyper-parameter optimization. Moreover, during evaluation, special attention will be given to the usefulness of made

KW - Knowledge Graphs

KW - Deep Learning

M3 - Poster

ER -

Wilcke WX. Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs. 2015. Poster session presented at ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal.