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

[Sarra Ben Abbès]

Dear colleagues and researchers,

Please consider contributing 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.

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                           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/

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*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
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, 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 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 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
<https://easychair.org/conferences/?conf=deepontonlp2022> submission page.

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
instructions please refer to the ESWC 2022
<https://2022.eswc-conferences.org/> page.
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: 30th of May, 2022 (afternoon-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
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