License: 
Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.AIB.2022.2
URN: urn:nbn:de:0030-drops-160005
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16000/
Guimarães, Ricardo ;
Ozaki, Ana
Reasoning in Knowledge Graphs (Invited Paper)
Abstract
Knowledge Graphs (KGs) are becoming increasingly popular in the industry and academia. They can be represented as labelled graphs conveying structured knowledge in a domain of interest, where nodes and edges are enriched with metaknowledge such as time validity, provenance, language, among others. Once the data is structured as a labelled graph one can apply reasoning techniques to extract relevant and insightful information. We provide an overview of deductive and inductive reasoning approaches for reasoning in KGs.
BibTeX - Entry
@InProceedings{guimaraes_et_al:OASIcs.AIB.2022.2,
author = {Guimar\~{a}es, Ricardo and Ozaki, Ana},
title = {{Reasoning in Knowledge Graphs}},
booktitle = {International Research School in Artificial Intelligence in Bergen (AIB 2022)},
pages = {2:1--2:31},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-228-0},
ISSN = {2190-6807},
year = {2022},
volume = {99},
editor = {Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2022/16000},
URN = {urn:nbn:de:0030-drops-160005},
doi = {10.4230/OASIcs.AIB.2022.2},
annote = {Keywords: Knowledge Graphs, Description Logics, Knowledge Graph Embeddings}
}
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Keywords: |
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Knowledge Graphs, Description Logics, Knowledge Graph Embeddings |
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Collection: |
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International Research School in Artificial Intelligence in Bergen (AIB 2022) |
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Issue Date: |
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2022 |
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Date of publication: |
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25.05.2022 |
