[DL] [Last CFP] 2nd International workshop on Deep Learning meets Ontologies and Natural Language Processing @ESWC-2021

[Rim Hantach]

Dear colleagues and researchers,



Please consider submitting a paper for the 2nd International workshop  "*Deep
Learning meets Ontologies and Natural Language Processing*"  which will be
held online or in Hersonissos, Greece - June 6th or 7th 2021.



** *DeepOntoNLP* -  Call for Papers ***

Deep Learning meets Ontologies and Natural Language Processing
(DeepOntoNLP) https://sites.google.com/view/deepontonlp-eswc2021

in conjunction with ESWC 2021 <https://2021.eswc-conferences.org/> online
or in Hersonissos, Greece



**Workshop description**

In recent years, deep learning is 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 analyse
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 has 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 recently 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 a 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 results of
on-going research in natural language processing, structured knowledge and
deep learning approaches.



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



**Topics of interests**

·       Construction ontology embeddings

·    Ontology-based text classification

·    Learning ontology embeddings

·    Semantic role labelling

·    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.google.com/url?q=https%3A%2F%2Fwww.springer.com%2Ffr%2Fcomputer-science%2Flncs%2Fconference-proceedings-guidelines&sa=D&sntz=1&usg=AFQjCNGhadQkou1B6uTwaCrX2p9HjIC9Iw>.
Papers are to be submitted through the Easychair Conference Management
System <https://easychair.org/conferences/?conf=deepontonlp2021>.

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 to the conference. For further
instructions please refer to the ESWC 2021
<https://www.google.com/url?q=https%3A%2F%2F2021.eswc-conferences.org%2F&sa=D&sntz=1&usg=AFQjCNEOdqEjLIkWyjAg16Zm5dm7MZ9kyg>
 page.

**Important dates**

   -

   Workshop paper submission due: *March 1st, 2021*
   -

   Workshop paper notifications: March 31st, 2021
   -

   Workshop paper camera-ready versions due: April 9th, 2021
   -

   Workshop: June 6th or 7th, 2021 (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 2021.



**Workshop chairs**


*Sarra BEN ABBES*, 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
Efstratios Kontopoulos, Catalink Ltd, Cyprus
Wei Hu, Nanjing University, China
Sanju Tiwari, Universidad Autonoma de Tamaulipas, Mexico
Linda Elmhadhbi, Université de Toulouse, France
Amir Laadhar, Aalborg University, Denmark
Yannis Haralambous, IMT Atlantique, France
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