<div dir="ltr"><div id="gmail-:5k5" class="gmail-a3s gmail-aiL"><div class="gmail-adM"><br></div><div><div><div><div><div><div dir="ltr">Dear colleagues and researchers,<div><div dir="ltr"><p>Please consider to contribute to the 3rd edition of the international workshop "<b>Deep Learning meets Ontologies and Natural Language Processing</b>" which will be held online or in Hersonissos, Greece - May 29 - June 2, 2022.</p><p>==============================<span></span>==============================<span></span>=============<br></p><p> The deadline for paper submissions is <span><b>March 18th, 2022</b></span></p><p>==============================<span></span>==============================<span></span>=============</p><p><b>DeepOntoNLP-2022</b><br></p><p>3rd International workshop on Deep Learning meets Ontologies and Natural Language Processing at <a href="https://2022.eswc-conferences.org/" target="_blank">ESWC 2022</a>, Hersonissos, Greece - May 29 - June 2, 2022<br>Workshop website: <a href="https://sites.google.com/view/deepontonlp2022/" target="_blank">https://sites.google.<span></span>com/view/deepontonlp2022/</a><br></p><p>==============================<span></span>==============================<span></span>============= <br></p><span dir="ltr"><div><span><span><span><strong>Context</strong></span></span></span></div></span><p dir="ltr"><span><span><span>In
recent years, deep learning has been applied successfully and achieved
state-of-the-art performance in a variety of domains, such as image
analysis. Despite this success, deep learning models remain hard to
analy</span><span>z</span><span>e data and understand what knowledge is represented in them, and how they generate decisions.</span></span></span></p><p dir="ltr"><span><span><span>Deep
Learning (DL) meets Natural Language Processing (NLP) to solve human
language problems for further applications, such as information
extraction, machine translation, search</span><span>, </span><span>and summarization. Previous works ha</span><span>ve</span><span> attested
the positive impact of domain knowledge on data analysis and vice
versa, for example pre-processing data, searching data, redundancy and
inconsistency data, knowledge engineering, domain concepts</span><span>, </span><span>and
relationships extraction, etc. Ontology is a structured knowledge
representation that facilitates data access (data sharing and reuse) and
assists the DL process as well. DL meets recent</span><span> </span><span>ontologies and tries to model data representations with many layers of non-linear transformations.</span></span></span></p><p dir="ltr"><span><span><span>The combination of DL, ontologies</span><span>, </span><span>and NLP might be beneficial for different tasks:</span></span></span></p><ul><li dir="ltr"><p dir="ltr"><span><span><span>Deep Learning for Ontologies: ontology population, ontology extension, ontology learning, ontology alignment</span><span>, </span><span>and integration,</span></span></span></p></li><li dir="ltr"><p dir="ltr"><span><span><span>Ontologies
for Deep Learning: semantic graph embeddings, latent semantic
representation, hybrid embeddings (symbolic and semantic
representations),</span></span></span></p></li><li dir="ltr"><p dir="ltr"><span><span><span>Deep Learning for NLP: summarization, translation, named entity recognition, question answering, document classification, etc.</span></span></span></p></li><li dir="ltr"><p dir="ltr"><span><span><span>NLP
for Deep Learning: parsing (part-of-speech tagging), tokenization,
sentence detection, dependency parsing, semantic role labeling, semantic
dependency parsing, etc.</span></span></span></p></li></ul><span dir="ltr"><div><span><span><span><strong>Objective</strong></span></span></span></div></span><p dir="ltr"><span><span><span>This</span><span> </span><span>workshop
aims at demonstrating recent and future advances in semantic rich deep
learning by using Semantic Web and NLP techniques which can reduce the
semantic gap between the data, applications, machine learning process,
in order to obtain semantic-aware approaches. In addition, the goal of
this workshop is to bring together an area for experts from industry,
science</span><span>, </span><span>and academia to exchange ideas and discuss the results of ongoing research in natural language processing, structured knowledge</span><span>, </span><span>and deep learning approaches.</span></span></span></p><p dir="ltr"><span><span><span>==============================<span></span>==============================<span></span>============<br></span></span></span></p></div></div></div></div></div></div></div></div><div><div><div><div><span><span><span><span><br><p dir="ltr"><span><span><span style="white-space:pre-wrap">We invite the submission of original works that are related -- but are not limited to -- the topics below.</span></span></span></p><span dir="ltr"><span><span><span style="white-space:pre-wrap">Topics of interest:</span></span></span></span><ul><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Construction ontology embeddings</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Ontology-based text classification</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Learning ontology embeddings</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Semantic role labeling</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Ontology reasoning with Deep Neural Networks</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Deep learning for ontological semantic annotations</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Spatial and temporal ontology embeddings</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Ontology alignment and matching based on deep learning models</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Ontology learning from text using deep learning models</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Unsupervised Learning</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Text classification using deep models</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Neural machine translation</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Deep question answering</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Deep text summarization</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Deep speech recognition</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>and so on.</span></span></span></p></li></ul><span dir="ltr"><span><span><span style="white-space:pre-wrap">Submission:</span></span></span></span><p dir="ltr"><span><span><span style="white-space:pre-wrap">The workshop is open to submitting unpublished work resulting from research that presents original scientific results, methodological aspects, concepts, and approaches. All submissions must be PDF documents written in English and formatted according to</span><a href="https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines" style="text-decoration-line:none" target="_blank"><span style="white-space:pre-wrap"> </span><span style="text-decoration-line:underline;white-space:pre-wrap">LNCS instructions for authors</span></a><span style="white-space:pre-wrap">. Papers are to be submitted through </span><span style="white-space:pre-wrap">the workshop's</span><a href="https://easychair.org/conferences/?conf=deepontonlp2022" style="text-decoration-line:none" target="_blank"><span style="text-decoration-line:underline;white-space:pre-wrap"> EasyChair</span></a><span style="white-space:pre-wrap"> submission page</span><span style="white-space:pre-wrap">.</span></span></span></p><p dir="ltr"><span><span><span style="white-space:pre-wrap">We welcome the following types of contributions:</span></span></span></p><ul><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Full research papers (8-10 pages): Finished or consolidated R&D works, to be included in one of the Workshop topics</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Short papers (4-6 pages): Ongoing works with relevant preliminary results, opened to discussion.</span></span></span></p></li></ul><p dir="ltr"><span><span><span style="white-space:pre-wrap">At least one author of each accepted paper must register for the workshop, in order to present the paper, there, and at the conference. For further instructions please refer to the</span><a href="https://2022.eswc-conferences.org/" style="text-decoration-line:none" target="_blank"><span style="text-decoration-line:underline;white-space:pre-wrap"> ESWC 2022</span></a><span style="white-space:pre-wrap"> page.</span></span></span></p><span dir="ltr"><span><span><span style="white-space:pre-wrap">Important dates:</span></span></span></span><ul><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Workshop paper submission due: March 18th, 2022</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Workshop paper notifications: April 15th, 2022</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Workshop paper camera-ready versions due: April 22th, 2022</span></span></span></p></li><li dir="ltr" style="white-space:pre-wrap"><p dir="ltr"><span><span><span>Workshop: 30th of May, 2022 (afternoon-Half-Day)</span></span></span></p></li></ul><p dir="ltr"><span><span><span style="white-space:pre-wrap">All deadlines are 23:59 anywhere on earth (UTC-12).</span></span></span></p><span dir="ltr"><span><span><span style="white-space:pre-wrap">Publication:</span></span></span></span><p dir="ltr"><span><span><span style="white-space:pre-wrap">The best papers from this workshop may be included in the supplementary proceedings of ESWC 2022.</span></span></span></p><p dir="ltr"><span><span><span style="white-space:pre-wrap">==============================<span></span>==============================<span></span>============</span></span></span></p><u><b><span dir="ltr"><span><span><span style="white-space:pre-wrap">Workshop Chairs</span></span></span></span></b></u><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap"> Sarra Ben Abbès</span><span style="white-space:pre-wrap">, </span><span style="white-space:pre-wrap">Engie, France</span></span></span></p><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap"> Rim Hantach</span><span style="white-space:pre-wrap">, </span><span style="white-space:pre-wrap">Engie, France</span></span></span></p><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap"> Philippe Calvez</span><span style="white-space:pre-wrap">, </span><span style="white-space:pre-wrap">Engie, France</span></span></span></p><p dir="ltr"><span><span><span style="white-space:pre-wrap"></span></span></span></p></span></span></span></span></div></div></div></div><div><div><div><div><div><div><div><div><div><div><div><span><span><span><span><br><div><div><div><div><div><div><div><div><div><div><div><div><div><span><span><span></span></span></span></div></div></div></div></div></div></div></div></div></div></div></div></div></span><span><u><b><span dir="ltr"><span><span><span style="white-space:pre-wrap">Program Committee</span></span></span><span><span><span style="white-space:pre-wrap"></span></span></span></span></b></u><span dir="ltr"><u><b> </b></u> <br></span></span></span></span></span></div><div><span><span><span><span><span dir="ltr"><br></span></span></span></span></span></div><div><span><span><span><span><span dir="ltr"><span><span><b><span style="white-space:pre-wrap">Nada Mimouni</span></b><span style="font-weight:400;white-space:pre-wrap"><b>,</b> CNAM, France</span><span style="white-space:pre-wrap"><br></span></span></span></span><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap">Lynda Temal</span><span style="white-space:pre-wrap">, Engie, France</span></span></span></p><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap">Davide Buscaldi</span><span style="white-space:pre-wrap">, LIPN, Université Sorbonne Paris Nord, France</span></span></span></p><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap">Valentina Janev</span><span style="white-space:pre-wrap">, Mihajlo Pupin Institute, Serbia</span></span></span></p><p dir="ltr"><span><span><span style="font-weight:700;white-space:pre-wrap">Mohamed Hedi Karray, </span><span style="white-space:pre-wrap">LGP-INP-ENIT, Université de Toulouse, France</span></span></span></p></span></span></span></span></div></div></div></div></div></div></div></div></div></div></div></div></div>