<div dir="ltr"><p class="MsoNormal" style="margin:0cm 0cm 12pt;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Dear colleagues and researchers,</span></font></p><p class="MsoNormal" style="margin:0cm 0cm 12pt;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif;text-align:center">Please consider submitting a paper for the 1st International workshop on
"Joint Use of Probabilistic Graphical Models and Ontology" which will be held online
- November 19-24, 2021.<br></span></font></p><p class="MsoNormal" style="text-align:center;margin:0cm 0cm 12pt;font-family:Calibri,sans-serif"><font size="6"><span style="color:rgb(153,0,255)"><b><span style="font-family:Arial,sans-serif" lang="EN-US">PGMOnto: </span></b></span><b><span style="font-family:Arial,sans-serif" lang="EN-US"><font color="#a64d79"><span style="color:rgb(153,0,255)">Joint Use of Probabilistic Graphical Models and Ontology</span><br></font></span></b></font></p><p class="MsoNormal" style="text-align:center;margin:0cm 0cm 12pt;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif">1st International Workshop, </span><span style="font-family:"Times New Roman",serif">in </span>conjunction<span style="font-family:"Times New Roman",serif"> with </span><a href="https://kgswc.org/" style="font-family:"Times New Roman",serif" target="_blank">KGSWC 2021</a></font></p><p class="MsoNormal" style="text-align:center;margin:0cm 0cm 12pt;font-family:Calibri,sans-serif"><font size="4">November 19- 24, 2021 - Online</font></p><p class="MsoNormal" style="text-align:center;margin:0cm 0cm 12pt;font-size:12pt;font-family:Calibri,sans-serif"><a href="https://kgswc.org/pgmonto2021/">https://kgswc.org/pgmonto2021/</a></p><br><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-family:"Times New Roman",serif" lang="EN-US"></span></b></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-family:"Times New Roman",serif" lang="EN-US"><br></span></b></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><font size="4"><b><span style="font-family:"Times New Roman",serif" lang="EN-US">Important dates:</span></b></font><span style="font-family:"Times New Roman",serif" lang="EN-US"><br>
<font size="4">• Workshop paper submission due: <b><span style="background:yellow none repeat scroll 0% 0%">October 01, 2021</span></b><br>
• Workshop paper notifications: October 23, 2021<br>
• Workshop paper camera-ready versions due: November 02, 2021<br>
• Workshop: November 19-24, 2021 (half-day)</font></span></p><p class="MsoNormal" style="margin:0cm 0cm 12pt;font-size:12pt;font-family:Calibri,sans-serif"><font size="4">
<span style="font-family:"Times New Roman",serif" lang="EN-US">All deadlines are 23:59
anywhere on earth (UTC-12).</span></font><b><br></b></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US">Context of the workshop:</span></b></p><div><font size="4"><span style="font-family:times new roman,serif">An ontology is well known to be the best way to represent knowledge
in a domain of discourse. It is defined by Gruber as “an explicit
specification of a conceptualization”. It allows 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 resolve many challenging problems related
to the information domain (e.g., semantic interoperability among systems,
knowledge sharing, and knowledge capitalization). Ontology formalization
can be based on First order logic (FOL) to describe concepts,
relationships, and constraints, enabling it to make inferences and
giving it a graphical representation. Using ontology has many
advantages, among them we can cite ontology reusing, reasoning and
explanation, commitment, and agreement on a domain of discourse,
ontology evolution and mapping, etc.</span></font><font size="4"><span style="font-family:times new roman,serif">
</span></font></div><p><font size="4"><span style="font-family:times new roman,serif">Over the last three decades, graphical probabilistic models (PGMs)
have enjoyed a surge of interest as a practically feasible framework of
expert knowledge encoding and as a new comprehensive data analysis
framework.</span></font></p><font size="4"><span style="font-family:times new roman,serif">
</span></font><p><font size="4"><span style="font-family:times new roman,serif">Probabilistic graphical models (PGMs) such as Bayesian network,
influence diagram or probabilistic relational model are considered as
one of the most successful tools that enable a compact representation of
complex systems and the increased ability to effectively learn and
perform inference in large networks. Besides the compact representation
of probability, PGMs are also intuitively easier for a human to
understand than joint probabilities because they highlight the direct
dependencies between random variables and their overall semantics is
easily captured visually through their graphical representation.</span></font></p><font size="4"><span style="font-family:times new roman,serif">
</span></font><p><font size="4"><span style="font-family:times new roman,serif">In practice, the combination of PGMs and ontologies might be
beneficial to have high expressiveness and reasoning possibilities under
uncertainty. Despite the difference between these two domain
representation models, they have the potential to complement each other:
part of the value of ontology baseline knowledge may be used to enhance
PGM by resolving challenging tasks: (i) the identification of relevant
variables (variable selection), (ii) the determination of structural
relationships between the considered variables (arcs), and (iii) the
estimation of parameters associated to the model. Once the PGM is
learned, its results can be used together with an ontology reasoning engine
to perform probabilistic inference.</span></font></p><font size="4"><span style="font-family:times new roman,serif">
</span></font><p><font size="4"><span style="font-family:times new roman,serif">This first regular workshop aims at demonstrating recent and future
advances in Semantic Probabilistic Graphical Models and Probabilistic
Ontologies. Moreover, this workshop offers an invaluable opportunity to
boost collaboration and conversation between Industrial Experts and
academic researchers, allowing therefore exchanging ideas and presenting
results of on-going research in structured knowledge and causality
approaches.</span></font></p><p style="margin:0cm 0cm 7.5pt;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;box-sizing:border-box;font-size:12pt;font-family:"Times New Roman",serif"><span lang="EN-US"></span></p><p style="margin:0cm 0cm 7.5pt;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:12pt;font-family:"Times New Roman",serif"><b><span style="font-size:14pt" lang="EN-US">Objective:</span></b></p><p style="margin:0cm 0cm 7.5pt;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-family:"Times New Roman",serif"><font size="4"><span lang="EN-US">We invite submission of papers describing innovative research and
applications around the following topics. Papers that introduce new
theoretical concepts or methods, help to develop a better understanding
of new emerging concepts through extensive experiments, or demonstrate a
novel application of these methods to a domain are encouraged.</span></font></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US">Topics of interests</span></b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US">: </span><span style="font-family:"Times New Roman",serif" lang="EN-US"><br></span></p><ul><li><font size="4"><span style="font-family:times new roman,serif">Construction of probabilistic ontologies</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Construction of semantic probabilistic graphical model</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Semantic causality and probability</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Causality and ontology</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">PGM for ontology mapping</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">PGM learning</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Ontology for PGM construction</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Probabilistic inference engine</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">Tools, systems and applications</span></font></li><li><font size="4"><span style="font-family:times new roman,serif">and so on. <br></span></font></li></ul><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US">Submission:</span></b></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">The workshop is open to submit 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 style="color:rgb(5,99,193);text-decoration-line:underline"><span style="color:rgb(68,114,196)" lang="EN-US"><a href="http://www.springer.com/%20computer/lncs/lncs+authors?SGWID=0-40209-0-0-0?SGWID=0-40209-0-0-0" style="color:rgb(5,99,193)" target="_blank"><span style="font-family:"Times New Roman",serif;color:rgb(68,114,196)">KGSWC2021_authors_kit</span></a></span></span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Papers are to be submitted through the
workshop's </span><a href="https://easychair.org/conferences/?conf=pgmonto2021"><u><span style="font-family:"Times New Roman",serif"></span></u></a><u><a style="color:rgb(5,99,193)" target="_blank"><span lang="EN-US">EasyChair</span></a></u><span style="font-family:"Times New Roman",serif" lang="EN-US"> submission page.</span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">We welcome the following types of contributions:</span></font></p><ul style="margin-top:0cm;margin-bottom:0cm" type="square"><li class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><b><span style="font-family:"Times New Roman",serif" lang="EN-US">Full papers</span></b><span style="font-family:"Times New Roman",serif" lang="EN-US"> (8-10 pages):
Finished or consolidated R&D works, to be included in one of the
Workshop topics.</span></font></li><li class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><b><span style="font-family:"Times New Roman",serif" lang="EN-US">Short papers</span></b><span style="font-family:"Times New Roman",serif" lang="EN-US"> (6-8 pages): Ongoing
works with relevant preliminary results, opened to discussion.</span></font></li></ul><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">
</span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">At least one author of each accepted paper must
register for the workshop, in order to present the paper. For further
instructions, please refer to the </span><u><span style="font-family:"Times New Roman",serif"><a href="https://kgswc.org/" style="color:rgb(5,99,193)" target="_blank"><span lang="EN-US">KGSWC 2021</span></a></span></u><span style="font-family:"Times New Roman",serif" lang="EN-US"> page.</span></font></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><span style="font-family:"Times New Roman",serif" lang="EN-US"><br></span></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US">Workshop chairs:</span></b></p><p class="MsoNormal" style="margin:0cm;font-size:12pt;font-family:Calibri,sans-serif"><b><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US"></span><span style="font-size:14pt;font-family:"Times New Roman",serif" lang="EN-US"></span></b><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Sarra Ben Abbès, Engie, France</span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Ahmed Mabrouk, Engie, France</span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Lynda Temal, Engie, France</span></font></p><p class="MsoNormal" style="margin:0cm;font-family:Calibri,sans-serif"><font size="4"><span style="font-family:"Times New Roman",serif" lang="EN-US">Philippe Calvez, Engie, France</span></font></p></div>