<div dir="ltr"><div dir="ltr"><span>Dear colleagues and researchers,<span></span></span>

<p><span>Please consider contributing to the 2nd edition of the
international workshop "<b> Ontology Uses and Contribution to
Artificial Intelligence</b> ", in conjunction with </span><i><span><span> </span></span></i><a href="http://www.pakdd.net/" target="_blank"><b><span>PAKDD 2022</span></b></a><b><span> </span></b><span>which will be held online or in Chengdu, China - May 16 - 19, 2022.<span></span></span></p>

<div><br></div>

<p><span>==================================================================<span></span></span></p>

<p><span>                          
The deadline for paper submissions is <span style="background-color:rgb(255,255,0)"><b><span>March 11, 2022</span></b></span><span></span></span></p>

<p><span>==================================================================<span></span></span></p>

<p><b><span>OnUCAI-2022</span></b><span><span></span></span></p>

<p><span>2nd International workshop
on Ontology Uses and Contribution to Artificial Intelligence at </span><a href="http://www.pakdd.net/" target="_blank"><b><span>PAKDD 2022</span></b></a><span>, Chengdu,
China - May 16 - 19, 2022<br>
Workshop website: </span><a href="https://sites.google.com/view/onucai-pakdd-2022" target="_blank"><span>https://sites.google.com/view/onucai-pakdd-2022</span></a><span><span></span></span></p>

<p><span>==================================================================<span></span></span></p>

<p><b><span>Context<span style="background-color:rgb(255,255,0)"><span></span></span></span></b><b><span><span></span></span></b></p>

<p><span>An ontology is well known to be the best way to
represent knowledge in a domain of interest. It is defined by Gruber and
Guarino as “an explicit specification of a conceptualization”. It allows us to
represent explicitly and formally existing entities, their relationships, and
their constraints in an application domain. This representation is the most
suitable and beneficial way to solve many challenging problems related to the
information domain (e.g., knowledge representation, knowledge sharing,
knowledge reusing, automated reasoning, knowledge capitalizing, and ensuring
semantic interoperability among heterogeneous systems). Using ontology has many
advantages, among them we can cite ontology reusing, reasoning, explanation,
commitment, and agreement on a domain of discourse, ontology evolution,
mapping, etc. As a field of artificial intelligence (AI), ontology aims at
representing knowledge based on declarative and symbolic formalization.
Combining this symbolic field with computational fields of IA such as Machine
Learning (ML), Deep Learning (DL), Uncertainty and Probabilistic Graphical
Models (PGMs), Computer Vision (CV), Multi-Agent Systems (SMA) and Natural
Languages Processing (NLP) is a promising association. Indeed, ontological
modeling plays a vital role to help AI reduce the complexity of the studied
domain and organizing information inside it. It broadens AI’s scope allowing it
to include any data type as it supports unstructured, semi-structured, or
structured data format which enables smoother data integration. The ontology
also assists AI for the interpretation process, learning, enrichment,
prediction, semantic disambiguation, and discovery of complex inferences. Finally,
the ultimate goal of ontologies is the ability to be integrated into the
software to make sense of all information.<span></span></span></p>

<p><span>In the last decade, ontologies are increasingly
being used to provide background knowledge for several AI domains in different
sectors (e.g. energy, transport, health, banking, insurance, etc.). Some of
these AI domains are:<span></span></span></p>

<ul><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Machine learning and deep learning:
semantic data selection, semantic data pre-processing, semantic data
transformation, semantic data prediction, semantic clustering correction of the
outputs, semantic enrichment with ontological concepts, use the semantic
structure for promoting distance measure, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Uncertainty and Probabilistic
Graphical Models: learning PGM (structure or parameters) using ontologies,
probabilistic semantic reasoning, semantic causality, probability, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Computer Vision: semantic image
processing, semantic image classification, semantic object
recognition/classification, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Blockchain: semantic transactions,
interoperable blockchain systems, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Natural Language Processing:
semantic text mining, semantic text classification, semantic role labeling,
semantic machine translation, semantic question answering, ontology-based text
summarizing, semantic recommendation systems, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Multi-Agent Systems and Robotics:
semantic task composition, task assignment, communication, cooperation,
coordination, plans, and plannification, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Voice-video-speech: semantic voice
recognition, semantic speech annotation, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>Game Theory: semantic definition of
specific games, semantic rules and goals definition, etc.<span></span></span></li><li><span><span><span style="font-weight:normal;font-style:normal">  </span></span></span><span>etc.<span></span></span></li></ul>

<p><b><span>Objective<span></span></span></b></p>

<p><span>This workshop aims at highlighting recent and future advances on the
role of ontologies and knowledge graphs in different domains of AI and how they
can be used in order to reduce the semantic gap between the data, applications,
machine learning process, etc., 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 ontologies and AI approaches.<span></span></span></p>

<p><span>========================================================================</span><span><span></span></span></p><span><span><span><span></span></span></span></span><span><span><span><span><p><span>We invite
  the submission of original works that are related -- but are not limited to
  -- the topics below.<span></span></span></p></span></span></span></span><span><span><span><span></span></span></span></span><span><span><span><span>
  <p><b><span>Topics of interest:<span></span></span></b></p></span></span></span></span><span><span><span><span><p><span>* Ontology for Machine Learning/Deep Learning<span></span></span></p></span></span></span></span><span><span><span><span><p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Uncertainty and Probabilistic Graphical Models<span></span></span><br><span><span><span><span>
  </span></span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Edge Computing<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Federated Machine Learning<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Smart Contracts<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Computer Vision<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Natural Language Processing<span></span></span></p></span></span></span></span><span><span><span><span><p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Robotics and Multi-agent Systems<span></span></span></p></span></span></span></span><span><span><span><span></span></span></span></span><span><span><span><span></span></span></span></span><span><span><span><span></span></span></span></span><span><span><span><span>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Voice-video-speech<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* Ontology for Game Theory<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><span>* and so on.<span></span></span></p></span></span></span></span><span><span><span><span><p><b><span>Submission:<span></span></span></b></p>
  <p><span>The
  workshop is open to submitting unpublished work resulting from research that
  presents original scientific results, methodological aspects, concepts, and
  approaches. All submissions are not anonymous and must be PDF documents
  written in English and formatted using the following style files:</span><span>
  </span><a href="https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines" target="_blank"><span>PAKDD2022_authors_kit</span></a><span>  </span><span><span></span></span></p>
  <p><span>Papers
  are to be submitted through the workshop's</span><span> </span><a href="https://tobedefined" target="_blank"><span>CMT3</span></a><span><span> </span></span><span>submission
  page</span><span>.</span><span><span></span></span></p>
  <p><span>We
  welcome the following types of contributions:<span></span></span></p>
  <p><span><span>* <span style="font-weight:normal;font-style:normal"></span></span></span><b><span>Full papers</span></b><span> of up to 9 pages, including
  abstract, figures, and appendices (if any), but excluding references and
  acknowledgments: Finished or consolidated R&D works, to be included in
  one of the Workshop topics.<span></span></span></p>
  <p><span><span><span style="font-weight:normal;font-style:normal"></span></span></span><b><span>* Short papers</span></b><span> of up to 4 pages, excluding
  references and acknowledgments: Ongoing works with relevant preliminary
  results, opened to discussion.<span></span></span></p>
  <p><span>Submitting a paper to the
  workshop means that the authors agree that at least one author should attend
  the workshop to present the paper if the paper is accepted. For no-show
  authors, their affiliations will receive a notification. For further
  instructions, please refer to the</span><span> </span><a href="http://www.pakdd.net/" target="_blank"><span>PAKDD 2022</span></a><span>
  </span><span>page.<span></span></span></p>
  <p><b><span>Important dates:<span></span></span></b></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> </span></span></span><span>Workshop
  paper submission due: <b><span>March 11, 2022<span></span></span></b></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span><span>Workshop paper notifications: March 31, 2022<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> </span></span></span><span>Workshop paper camera-ready versions due: April 15, 2022<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> </span></span></span><span>Workshop: May 16-19, 2022 (Half-Day)<span></span></span></p>
  <p><span>All deadlines are 23:59 anywhere on earth
  (UTC-12).<span></span></span></p>
  <p><b><span>Publication:<span></span></span></b></p>
  <p><span>The accepted papers of this workshop may be included in the
  Proceedings of PAKDD 2022 Workshops published by Springer.</span><span><span></span></span></p>
  <p><span>=================================================================<span></span></span></p>
  <p><b><span>Workshop Chairs<span></span></span></b></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Sarra Ben Abbès, Engie, France<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Lynda Temal, Engie, France<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> </span></span></span><span>Nada Mimouni, CNAM, France<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Ahmed Mabrouk, Engie, France<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Philippe Calvez, Engie, France<span></span></span></p></span></span></span></span><span><span><span><span><p><b><span>Program Committee<span></span></span></b></p></span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span></span></span></span><span><span><span><span></span></span></span></span><span><span><span><span>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span>Shridhar Devamane, Physical Design Engineer,
  Tecsec Technologies, Bangalore, India<span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span>Oudom Kem, Researcher at Engie, France<span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Philippe Leray, Professor at
  University of Nantes <span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Stefan Fenz, key researcher at SBA
  Research and Senior Scientist at</span><span style="text-decoration:none"> Vienna University of Technology</span><span><span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span>Olivier Dameron, Professor at Université de
  Rennes I, Dyliss team, Irisa / Inria Rennes-Bretagne
  Atlantique   <span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Ammar Mechouche, Data Science
  expert at AIRBUS Helicopters <span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>Aarón Ayllón Benitez, PhD in
  bioinformatics and Ontology Lead at BASF Digital Solutions S.L.<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span><span>François Scharffe, Researcher on
  Knowledge-based AI, New York, United States<span></span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span>Maxime Lefrançois, Associate Professor at
  Saint Etienne University, France <span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal"> 
  </span></span></span>Pierre Maret, The QA Company & Saint
  Etienne University, France<span></span></p>
  <p><span><span>*<span style="font-weight:normal;font-style:normal">  </span></span></span>Sanju Tiwari, Universidad Autonoma de
  Tamaulipas, Mexico</p></span></span></span></span></div></div>