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Final CfP: 1st Workshop on Semantic Explainability (SemEx 2019), co-located with ICSC 2019

From: Basil Ell <bell@techfak.uni-bielefeld.de>
Date: Fri, 16 Nov 2018 23:18:09 +0100
To: semantic-web@w3.org
Message-ID: <1f8bd89c-b0c3-7669-86c0-5c58cb421724@techfak.uni-bielefeld.de>
*10 days left* to submit to the 1st Workshop on Semantic Explainability 
(SemEx 2019).

Submission deadline: *Nov 26, 2018* – 23:59 Hawaii Time

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                                                           Final Call 
For Research Papers
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                                          1st Workshop on Semantic 
Explainability (SemEx 2019)
http://www.semantic-explainability.com/

co-located with
                           The 13th IEEE International Conference on 
Semantic Computing (ICSC 2019)
                                         Jan 30 - Feb 1, 2019 - Newport 
Beach, California, USA

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Overview
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In recent years, the explainability of complex systems such as decision 
support systems, automatic decision systems, machine 
learning-based/trained systems, and artificial intelligence in general 
has been expressed not only as a desired property, but also as a 
property that is required by law. For example, the General Data 
Protection Regulation’s (GDPR) „right to explanation“ demands that the 
results of ML/AI-based decisions are explained. The explainability of 
complex systems, especially of ML-based and AI-based systems, becomes 
increasingly relevant as more and more aspects of our lives are 
influenced by these systems‘ actions and decisions.

Several workshops address the problem of explainable AI. However, none 
of these workshops has a focus on semantic technologies such as 
ontologies and reasoning. We believe that semantic technologies and 
explainability coalesce in two ways. First, systems that are based on 
semantic technologies must be explainable like all other AI systems. In 
addition, semantic technologies seem predestined to support rendering 
systems that are not based on semantic technologies explainable.

Turning a system that already makes use of ontologies into an 
explainable system could be supported by the ontologies, as ideally the 
ontologies capture some aspects of the users‘ conceptualizations of a 
problem domain. However, how can such systems make use of these 
ontologies to generate explanations of actions they performed and 
decisions they took? Which criteria must an ontology fulfill so that it 
supports the generation of explanations? Do we have adequate ontologies 
that enable to express explanations and enable to model and reason about 
what is understandable or comprehensible for a certain user? What kind 
of lexicographic information is necessary to generate linguistic 
utterances? How to evaluate a system‘s understandability? How to design 
ontologies for system understandability? What are models of 
human-machine interaction where the system enables to interact with the 
system until the user understood a certain action or decision? How can 
explanatory components be reused with other systems that they have not 
been designed for?

Turning systems that are not yet based on ontologies but on sub-symbolic 
representations/distributed semantics such as deep learning-based 
approaches into explainable systems might be supported by the use of 
ontologies. Some efforts in this field have been referred to as 
neural-symbolic integration.

This workshop aims to bring together international experts interested in 
the application of semantic technologies for explainability of 
artificial intelligence/machine learning to stimulate research, 
engineering and evaluation – towards making machine decisions 
transparent, re-traceable, comprehensible, interpretable, explainable, 
and reproducible. Semantic technologies have the potential to play an 
important role in the field of explainability since they lend themselves 
very well to the task, as they enable to model users‘ conceptualizations 
of the problem domain. However, this field has so far only been only 
rarely explored.

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                                                            Topics of 
Interest
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Topics of interest include, but are not limited to:

- Explainability of machine learning models based on semantics/ontologies
- Exploiting semantics/ontologies for explainable/traceable recommendations
- Explanations based on semantics/ontologies in the context of decision 
making/decision support systems
- Semantic user modelling for personalized explanations
- Design criteria for explainability-supporting ontologies
- Dialogue management and natural language generation based on 
semantics/ontologies
- Visual explanations based on semantics/ontologies
- Multi-modal explanations using semantics/ontologies
- Interactive/incremental explanations based on semantics/ontologies
- Ontological modeling of explanations and user profiles

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                                                          Author 
Instructions
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Manuscripts should be prepared according to the IEEE ICSC Author 
Guidelines (Go Here for Formatting Guideline, LaTex Styles and Word 
Template: https://www.ieee-icsc.org/submission). Submissions must be in 
English, must not be longer than eight (8) pages, must be provided as a 
PDF file, and must be submitted using the SemEx 2019 EasyChair 
(https://easychair.org/conferences/?conf=semex2019) site.

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                                                          Important Dates
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Submission deadline: Nov 26, 2018 – 23:59 Hawaii Time
Notification of acceptance: Dec 10, 2018 – 23:59 Hawaii Time
Camera-ready version due: Dec 17, 2018 – 23:59 Hawaii Time
Workshop Date: Jan 30, 2019 (subject to conference schedule)

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                                                      Workshop Organizers
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Philipp Cimiano – Bielefeld University
Basil Ell – Bielefeld University, Oslo University
Axel-Cyrille Ngonga Ngomo – Paderborn University

-- 

Dr. Basil Ell
AG Semantic Computing
Bielefeld University
Bielefeld, Germany
CITEC, 2.311
+49 521 106 2951



-- 

Dr. Basil Ell
AG Semantic Computing
Bielefeld University
Bielefeld, Germany
CITEC, 2.311
+49 521 106 2951
Received on Friday, 16 November 2018 22:18:38 UTC

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