Connectionists: 3rd International workshop on Deep Learning meets Ontologies and Natural Language Processing @ESWC 2022

[Sarra Ben Abbès]

Dear colleagues and researchers,

Please consider to contribute to the 3rd edition of the international
workshop
"*Deep Learning meets Ontologies and Natural Language Processing*"
which will be held online or in Hersonissos, Greece
May 29 - June 2, 2022.

=======================================================================

     The deadline for paper submissions is *March 18th, 2022*

=======================================================================

*DeepOntoNLP-2022*

3rd International workshop on Deep Learning meets Ontologies and
Natural Language Processing at ESWC 2022
https://2022.eswc-conferences.org/, Hersonissos, Greece
May 29 - June 2, 2022
Workshop website: https://sites.google.com/view/deepontonlp2022/

=======================================================================

*Context*

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 analyze data and understand what knowledge is represented in them,
and how they generate decisions.

Deep Learning (DL) meets Natural Language Processing (NLP) to solve
human language problems for further applications, such as information
extraction, machine translation, search, and summarization. Previous
works have 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, 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 ontologies
and tries to model data representations with many layers of non-linear
transformations.

The combination of DL, ontologies, and NLP might be beneficial for
different tasks:

    -    Deep Learning for Ontologies: ontology population, ontology
         extension, ontology learning, ontology alignment, and
         integration,
    -    Ontologies for Deep Learning: semantic graph embeddings, latent
         semantic representation, hybrid embeddings (symbolic and
         semantic representations),
    -    Deep Learning for NLP: summarization, translation, named entity
         recognition, question answering, document classification, etc.
    -    NLP for Deep Learning: parsing (part-of-speech tagging),
         tokenization, sentence detection, dependency parsing, semantic
         role labeling, semantic dependency parsing, etc.

*Objective*

This 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, 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, and academia to exchange ideas and
discuss the results of ongoing research in natural language processing,
structured knowledge, and deep learning approaches.

=======================================================================


We invite the submission of original works that are related -- but are
not limited to -- the topics below.

Topics of interest:

    -    Construction ontology embeddings
    -    Ontology-based text classification
    -    Learning ontology embeddings
    -    Semantic role labeling
    -    Ontology reasoning with Deep Neural Networks
    -    Deep learning for ontological semantic annotations
    -    Spatial and temporal ontology embeddings
    -    Ontology alignment and matching based on deep learning models
    -    Ontology learning from text using deep learning models
    -    Unsupervised Learning
    -    Text classification using deep models
    -    Neural machine translation
    -    Deep question answering
    -    Deep text summarization
    -    Deep speech recognition
    -    and so on.

Submission:

The workshop is open to submit 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 LNCS instructions for authors
https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines
.
Papers are to be submitted through the workshop's EasyChair submission
page: https://easychair.org/conferences/?conf=deepontonlp2022.

We welcome the following types of contributions:

    -    Full research papers (8-10 pages): Finished or consolidated R&D
         works, to be included in one of the Workshop topics
    -    Short papers (4-6 pages): Ongoing works with relevant preliminary
         results, opened to discussion.

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 please refer to the ESWC 2022 page:
https://2022.eswc-conferences.org/

Important dates:

    -    Workshop paper submission due: March 18th, 2022
    -    Workshop paper notifications: April 15th, 2022
    -    Workshop paper camera-ready versions due: April 22th, 2022
    -    Workshop: 28th or the 29th of May, 2022 (Half-Day)

All deadlines are 23:59 anywhere on earth (UTC-12).

Publication:

The best papers from this workshop may be included in the supplementary
proceedings of ESWC 2022.

=======================================================================
Workshop Chairs

     Sarra Ben Abbès, Engie, France
     Rim Hantach, Engie, France
     Philippe Calvez, Engie, France


Program Committee
     Nada Mimouni, CNAM, France
     Lynda Temal, Engie, France
     Davide Buscaldi, LIPN, Université Sorbonne Paris Nord, France
     Valentina Janev, Mihajlo Pupin Institute, Serbia
     Mohamed Hedi Karray, LGP-INP-ENIT, Université de Toulouse, France
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20211223/4552aec7/attachment.html>