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#nodeclassification

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Pierre Monnin<p>Our paper "PyGraft: Configurable Generation of Synthetic <a href="https://sigmoid.social/tags/Schemas" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Schemas</span></a> and <a href="https://sigmoid.social/tags/KnowledgeGraphs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KnowledgeGraphs</span></a> at Your Fingertips" has been accepted in <span class="h-card" translate="no"><a href="https://sigmoid.social/@eswc_conf" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>eswc_conf</span></a></span> <a href="https://sigmoid.social/tags/ESWC2024" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ESWC2024</span></a>!</p><p>Paper: <a href="https://arxiv.org/pdf/2309.03685.pdf" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/pdf/2309.03685.pdf</span><span class="invisible"></span></a><br>Code: <a href="https://github.com/nicolas-hbt/pygraft" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/nicolas-hbt/pygraft</span><span class="invisible"></span></a></p><p>PyGraft is a configurable <a href="https://sigmoid.social/tags/Python" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Python</span></a> tool to generate both synthetic <a href="https://sigmoid.social/tags/schemas" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>schemas</span></a> and <a href="https://sigmoid.social/tags/knowledgeGraphs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>knowledgeGraphs</span></a> easily, supporting several RDFS and OWL constructs. These <a href="https://sigmoid.social/tags/datasets" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>datasets</span></a> are useful for, e.g., <a href="https://sigmoid.social/tags/neurosymbolicAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>neurosymbolicAI</span></a>, <a href="https://sigmoid.social/tags/linkPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>linkPrediction</span></a>, <a href="https://sigmoid.social/tags/nodeClassification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nodeClassification</span></a>, <a href="https://sigmoid.social/tags/nodeClustering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nodeClustering</span></a>, <a href="https://sigmoid.social/tags/ontology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ontology</span></a> repairing</p>
Pierre Monnin<p>PyGraft will help you generate new and tailored benchmark KG <a href="https://sigmoid.social/tags/datasets" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>datasets</span></a> useful in various fields including but not limited to <a href="https://sigmoid.social/tags/neurosymbolicAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>neurosymbolicAI</span></a>, <a href="https://sigmoid.social/tags/linkPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>linkPrediction</span></a>, <a href="https://sigmoid.social/tags/nodeClassification" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nodeClassification</span></a>, <a href="https://sigmoid.social/tags/nodeClustering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nodeClustering</span></a>, <a href="https://sigmoid.social/tags/ontology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ontology</span></a> repairing, pattern mining, reasoning, scalability studies, etc.</p><p>Feel free to download, star, fork, share and tell us about any usage you foresee! We welcome all contributions or ideas to improve PyGraft! Looking forward to feedback from <a href="https://sigmoid.social/tags/semanticWeb" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>semanticWeb</span></a> <a href="https://sigmoid.social/tags/machineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machineLearning</span></a> and other communities!</p>
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