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#linkprediction

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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>
Harald Sack<p>2nd add on to our free MOOC lecture series on <a href="https://sigmoid.social/tags/KnowledgeGraphs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KnowledgeGraphs</span></a> is a colab notebook on knowledge graph completion with TransE through which my colleagues Ann Tan and <span class="h-card" translate="no"><a href="https://sigmoid.social/@MahsaVafaie" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>MahsaVafaie</span></a></span> will guide you in the video.<br><a href="https://sigmoid.social/tags/OpenHPI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenHPI</span></a> video: <a href="https://open.hpi.de/courses/knowledgegraphs2023/items/48Sn5Tr9RKo24RXu7OwgOz" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">open.hpi.de/courses/knowledgeg</span><span class="invisible">raphs2023/items/48Sn5Tr9RKo24RXu7OwgOz</span></a><br>youtube video: <a href="https://www.youtube.com/watch?v=IVTVzgCbHOw&amp;list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&amp;index=67" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">youtube.com/watch?v=IVTVzgCbHO</span><span class="invisible">w&amp;list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&amp;index=67</span></a><br>colab notebook: <a href="https://colab.research.google.com/drive/104ad-kusmzfYgkK_L8ETWUAjfdreE9e2#scrollTo=fQ08XPbaZgQ4" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">colab.research.google.com/driv</span><span class="invisible">e/104ad-kusmzfYgkK_L8ETWUAjfdreE9e2#scrollTo=fQ08XPbaZgQ4</span></a></p><p><span class="h-card" translate="no"><a href="https://sigmoid.social/@fizise" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fizise</span></a></span> <span class="h-card" translate="no"><a href="https://wisskomm.social/@fiz_karlsruhe" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fiz_karlsruhe</span></a></span> <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/kge" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>kge</span></a> <a href="https://sigmoid.social/tags/embeddings" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>embeddings</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/videolecture" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>videolecture</span></a> <a href="https://sigmoid.social/tags/video" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>video</span></a></p>
Harald Sack<p>Knowledge Graph Embeddings (KGEs) are a very useful tool for few- and zero-shot learning. Of course Link Prediction and <a href="https://sigmoid.social/tags/KnowledgeGraph" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KnowledgeGraph</span></a> Completion are the most prominent tasks for KGEs. My colleague Ann Tan and I will start our investigation of KGEs in this section of our free <a href="https://sigmoid.social/tags/kg2023" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>kg2023</span></a> lecture.<br>OpenHPI video: <a href="https://open.hpi.de/courses/knowledgegraphs2023/items/3xfeKrryLMeY45OXSwBd86" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">open.hpi.de/courses/knowledgeg</span><span class="invisible">raphs2023/items/3xfeKrryLMeY45OXSwBd86</span></a><br>youtube video: <a href="https://www.youtube.com/watch?v=UGmtYSCXsQk&amp;list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&amp;index=62" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">youtube.com/watch?v=UGmtYSCXsQ</span><span class="invisible">k&amp;list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&amp;index=62</span></a><br>slides: <a href="https://zenodo.org/records/10185280" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">zenodo.org/records/10185280</span><span class="invisible"></span></a><br><span class="h-card" translate="no"><a href="https://fedihum.org/@tabea" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>tabea</span></a></span> <span class="h-card" translate="no"><a href="https://fedihum.org/@sashabruns" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>sashabruns</span></a></span> <span class="h-card" translate="no"><a href="https://sigmoid.social/@MahsaVafaie" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>MahsaVafaie</span></a></span> <span class="h-card" translate="no"><a href="https://wisskomm.social/@fiz_karlsruhe" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fiz_karlsruhe</span></a></span> <span class="h-card" translate="no"><a href="https://sigmoid.social/@fizise" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fizise</span></a></span> <a href="https://sigmoid.social/tags/embeddings" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>embeddings</span></a> <a href="https://sigmoid.social/tags/linkprediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>linkprediction</span></a></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>
Harald Sack<p>As a 2nd topic of this last <a href="https://sigmoid.social/tags/ise2023" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ise2023</span></a> lecture, we were discussing <a href="https://sigmoid.social/tags/KnowledgeGraph" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KnowledgeGraph</span></a> Completion. Most simple approach for unsupervised <a href="https://sigmoid.social/tags/linkprediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>linkprediction</span></a> based on (here translation-based) knowledge graph embeddings was explained on the example of Isaac Asimov. <br>Slides: <a href="https://drive.google.com/file/d/1atNvMYNkeKDwXP3olHXzloa09S5pzjXb/view?usp=drive_link" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">drive.google.com/file/d/1atNvM</span><span class="invisible">YNkeKDwXP3olHXzloa09S5pzjXb/view?usp=drive_link</span></a><br><span class="h-card"><a href="https://sigmoid.social/@fizise" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fizise</span></a></span> <span class="h-card"><a href="https://sigmoid.social/@enorouzi" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>enorouzi</span></a></span> <a href="https://sigmoid.social/tags/scifi" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>scifi</span></a> <a href="https://sigmoid.social/tags/knowledgegraphs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>knowledgegraphs</span></a> <a href="https://sigmoid.social/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://sigmoid.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</span></a> <a href="https://sigmoid.social/tags/embeddings" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>embeddings</span></a></p>
Harald Sack<p>Topics of the last <a href="https://sigmoid.social/tags/ise2023" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ise2023</span></a> lecture; The Graph in <a href="https://sigmoid.social/tags/KnowledgeGraphs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>KnowledgeGraphs</span></a>, Knowledge Graph Completion, A Brief History of Large Language Models, and Knowledge Graphs and Large Language Models. I will highlight some topics with the upcoming toots...<br>Slides: <a href="https://drive.google.com/file/d/1atNvMYNkeKDwXP3olHXzloa09S5pzjXb/view?usp=drive_link" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">drive.google.com/file/d/1atNvM</span><span class="invisible">YNkeKDwXP3olHXzloa09S5pzjXb/view?usp=drive_link</span></a><br><a href="https://sigmoid.social/tags/llms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>llms</span></a> <a href="https://sigmoid.social/tags/languagemodels" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>languagemodels</span></a> <a href="https://sigmoid.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deeplearning</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/kgc" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>kgc</span></a> <a href="https://sigmoid.social/tags/lecture" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>lecture</span></a> <a href="https://sigmoid.social/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearning</span></a> <a href="https://sigmoid.social/tags/transformers" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>transformers</span></a> <a href="https://sigmoid.social/tags/gpt" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>gpt</span></a> <span class="h-card"><a href="https://sigmoid.social/@fizise" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>fizise</span></a></span> <span class="h-card"><a href="https://sigmoid.social/@enorouzi" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>enorouzi</span></a></span></p>
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