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Dear colleagues and researchers,<br>
<br>
Please consider to contribute to the 3rd edition of the international<br>
workshop<br>
"*<span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span> <span class="gmail-il">meets</span> <span class="gmail-il">Ontologies</span> and Natural Language Processing*"<br>
which will be held online or in Hersonissos, Greece<br>
May 29 - June 2, 2022.<br>
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<br>
The deadline for paper submissions is *March 18th, 2022*<br>
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<br>
*DeepOntoNLP-2022*<br>
<br>
3rd International workshop on <span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span> <span class="gmail-il">meets</span> <span class="gmail-il">Ontologies</span> and<br>
Natural Language Processing at ESWC 2022<br>
<a href="https://2022.eswc-conferences.org/" rel="noreferrer" target="_blank">https://2022.eswc-conferences.org/</a>, Hersonissos, Greece<br>
May 29 - June 2, 2022<br>
Workshop website: <a href="https://sites.google.com/view/deepontonlp2022/" rel="noreferrer" target="_blank">https://sites.google.com/view/deepontonlp2022/</a><br>
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<br>
*Context*<br>
<br>
In recent years, <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> has been applied successfully and<br>
achieved state-of-the-art performance in a variety of domains, such as<br>
image analysis. Despite this success, <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> models remain hard<br>
to analyze data and understand what knowledge is represented in them,<br>
and how they generate decisions.<br>
<br>
<span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span> (DL) <span class="gmail-il">meets</span> Natural Language Processing (NLP) to solve<br>
human language problems for further applications, such as information<br>
extraction, machine translation, search, and summarization. Previous<br>
works have attested the positive impact of domain knowledge on data<br>
analysis and vice versa, for example pre-processing data, searching<br>
data, redundancy and inconsistency data, knowledge engineering, domain<br>
concepts, and relationships extraction, etc. Ontology is a structured<br>
knowledge representation that facilitates data access (data sharing and<br>
reuse) and assists the DL process as well. DL <span class="gmail-il">meets</span> recent <span class="gmail-il">ontologies</span><br>
and tries to model data representations with many layers of non-linear<br>
transformations.<br>
<br>
The combination of DL, <span class="gmail-il">ontologies</span>, and NLP might be beneficial for<br>
different tasks:<br>
<br>
- <span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span> for <span class="gmail-il">Ontologies</span>: ontology population, ontology<br>
extension, ontology <span class="gmail-il">learning</span>, ontology alignment, and<br>
integration,<br>
- <span class="gmail-il">Ontologies</span> for <span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span>: semantic graph embeddings, latent<br>
semantic representation, hybrid embeddings (symbolic and<br>
semantic representations),<br>
- <span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span> for NLP: summarization, translation, named entity<br>
recognition, question answering, document classification, etc.<br>
- NLP for <span class="gmail-il">Deep</span> <span class="gmail-il">Learning</span>: parsing (part-of-speech tagging),<br>
tokenization, sentence detection, dependency parsing, semantic<br>
role labeling, semantic dependency parsing, etc.<br>
<br>
*Objective*<br>
<br>
This workshop aims at demonstrating recent and future advances in<br>
semantic rich <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> by using Semantic Web and NLP techniques<br>
which can reduce the semantic gap between the data, applications,<br>
machine <span class="gmail-il">learning</span>, in order to obtain semantic-aware approaches. In<br>
addition, the goal of this workshop is to bring together an area for<br>
experts from industry, science, and academia to exchange ideas and<br>
discuss the results of ongoing research in natural language processing,<br>
structured knowledge, and <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> approaches.<br>
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<br>
<br>
We invite the submission of original works that are related -- but are<br>
not limited to -- the topics below.<br>
<br>
Topics of interest:<br>
<br>
- Construction ontology embeddings<br>
- Ontology-based text classification<br>
- <span class="gmail-il">Learning</span> ontology embeddings<br>
- Semantic role labeling<br>
- Ontology reasoning with <span class="gmail-il">Deep</span> Neural Networks<br>
- <span class="gmail-il">Deep</span> <span class="gmail-il">learning</span> for ontological semantic annotations<br>
- Spatial and temporal ontology embeddings<br>
- Ontology alignment and matching based on <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> models<br>
- Ontology <span class="gmail-il">learning</span> from text using <span class="gmail-il">deep</span> <span class="gmail-il">learning</span> models<br>
- Unsupervised <span class="gmail-il">Learning</span><br>
- Text classification using <span class="gmail-il">deep</span> models<br>
- Neural machine translation<br>
- <span class="gmail-il">Deep</span> question answering<br>
- <span class="gmail-il">Deep</span> text summarization<br>
- <span class="gmail-il">Deep</span> speech recognition<br>
- and so on.<br>
<br>
Submission:<br>
<br>
The workshop is open to submit unpublished work resulting from research<br>
that presents original scientific results, methodological aspects,<br>
concepts, and approaches. All submissions must be PDF documents written<br>
in English and formatted according to LNCS instructions for authors<br>
<a href="https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines" rel="noreferrer" target="_blank">https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines</a>.<br>
Papers are to be submitted through the workshop's EasyChair submission<br>
page: <a href="https://easychair.org/conferences/?conf=deepontonlp2022" rel="noreferrer" target="_blank">https://easychair.org/conferences/?conf=deepontonlp2022</a>.<br>
<br>
We welcome the following types of contributions:<br>
<br>
- Full research papers (8-10 pages): Finished or consolidated R&D<br>
works, to be included in one of the Workshop topics<br>
- Short papers (4-6 pages): Ongoing works with relevant preliminary<br>
results, opened to discussion.<br>
<br>
At least one author of each accepted paper must register for the<br>
workshop, in order to present the paper, there, and at the conference.<br>
For further please refer to the ESWC 2022 page:<br>
<a href="https://2022.eswc-conferences.org/" rel="noreferrer" target="_blank">https://2022.eswc-conferences.org/</a><br>
<br>
Important dates:<br>
<br>
- Workshop paper submission due: March 18th, 2022<br>
- Workshop paper notifications: April 15th, 2022<br>
- Workshop paper camera-ready versions due: April 22th, 2022<br>
- Workshop: 28th or the 29th of May, 2022 (Half-Day)<br>
<br>
All deadlines are 23:59 anywhere on earth (UTC-12).<br>
<br>
Publication:<br>
<br>
The best papers from this workshop may be included in the supplementary<br>
proceedings of ESWC 2022.<br>
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Workshop Chairs<br>
<br>
Sarra Ben Abbès, Engie, France<br>
Rim Hantach, Engie, France<br>
Philippe Calvez, Engie, France<br>
<br>
<br>
Program Committee<br>
Nada Mimouni, CNAM, France<br>
Lynda Temal, Engie, France<br>
Davide Buscaldi, LIPN, Université Sorbonne Paris Nord, France<br>
Valentina Janev, Mihajlo Pupin Institute, Serbia<br>
Mohamed Hedi Karray, LGP-INP-ENIT, Université de Toulouse, France</div>