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Keynote Lectures

IC3K is a joint conference composed of three concurrent conferences: KDIR, KEOD and KMIS. These three conferences are always co-located and held in parallel. Keynote lectures are plenary sessions and can be attended by all IC3K participants.

The AI System DLV: Ontologies, Reasoning, and More
Nicola Leone, University of Calabria, Italy

Knowledge Graph for Public Safety: Construction, Reasoning and Case Studies
Xindong Wu, Mininglamp Software Systems, China and University of Louisiana at Lafayette, United States

Building a Self-service IoT Analytics Toolbox: Basics, Models and Lessons Learned
Rudi Studer, Karlsruhe Institute of Technology, Germany

From Image Understanding to Text Description and Return - Deep Learning Paradigms for Annotation and Retrieval
Rita Cucchiara, University of Modena and Reggio Emilia, Italy (* Cancelled due to unforeseen unavailability of the speaker)

Conceptual Modelling and Web Applications: How to Make it a Right Partnership?
Oscar Pastor, Universidad Politécnica de Valencia, Spain


Knowledge Engineering through Process Mining - The Practice

Linda Terlouw
ICRIS Consultancy, Antwerp Management School, Avans University of Applied Sciences, Nyenrode Business University

Brief Bio
Dr. ir. Linda Terlouw holds both an MSc in Computer Science and an Msc in Business Information from the University of Twente. Her PhD research focused on modularization of organizations and IT systems using Enterprise Ontology and Service-Oriented Architecture. At the moment she is mainly working on data science (e.g. forecasting), data visualization and process mining (www.processminingfactory.com). Before she started her own company, Icris, she worked for IBM and Ordina (a large Dutch consulting firm). Clients she has been working for include several Dutch water suppliers, a large municipality, several factories, and the Ministry of Defense. She is lector (professor) at the Avans University of Applied Sciences and teaches at Nyenrode Business University and Antwerp Management School.


Large organizations often lack insight into the performance of their business processes, making it difficult to improve them. Process mining is an interdisciplinary field combining techniques from business process management and data science. It can, for instance, be used to check compliance of processes and to gain insight into bottlenecks in business processes. This lecture focuses on the problems and successes encountered in the practice of process mining. The main message is illustrated by various practical experiences.



The Role of Software Operation Knowledge in Software Ecosystems

Slinger Jansen
Utrecht University

Brief Bio

Slinger Jansen is a senior researcher at the Department of Information and Computer Science at Utrecht University. He is one of the leading researchers in the domain of software ecosystems and co-founders of the International Conference on Software Business, the Workshop on Ecosystem Architecture, and the International Workshop on Software Ecosystems. He is lead editor of the book “Software Ecosystems: Analyzing and Managing Business Networks in the Software Industry” and of several others. Besides his academic endeavors he actively supports new enterprises and sits on the boards of advisors of several start-ups, one of which is ThinkEcosystems.com.

Increasingly, software producing organizations collaborate in networks that have become known as software ecosystems. The intricate structures of platforms upon platforms enable rapid innovation like never before. In this talk, we explore how these platforms collect knowledge about the platform itself, the applications running on it, and the end-users that make use of these applications. Through examples and case studies is shown that software operation knowledge in software ecosystems is essential for creating better software, happier users, and more productive developers.



Type-2 Fuzzy Systems for Human Decision Making

Jonathan Garibaldi
University of Nottingham
United Kingdom

Brief Bio
Professor Jon Garibaldi received the BSc degree in Physics from University of Bristol, UK, in 1984, and MSc degree and PhD degree from the University of Plymouth, UK, in 1990 and 1997, respectively. Prof. Garibaldi is currently Head of School of Computer Science, University of Nottingham, Head of the Intelligent Modelling and Analysis (IMA) Research Group, Member of the Lab for Uncertainty in Data and Decision Making (LUCID) and joint Director of the Advanced Data Analysis Centre (ADAC). His main research interests include modelling uncertainty and variation in human reasoning, and in modelling and interpreting complex data to enable better decision making, particularly in medical domains. Prof. Garibaldi is the current Editor-in-Chief of IEEE Transactions on Fuzzy Systems. He has served regularly in the organising committees and programme committees of a range of leading international conferences and workshops, such as FUZZ-IEEE, WCCI, EURO and PPSN.

Type-2 fuzzy sets and systems, including both interval and general type-2 sets, are now firmly established as tools for the fuzzy researcher that may be deployed on a wide range of applications and in a wide set of contexts. However, in many situations the output of type-2 systems are type-reduced and then defuzzified to an interval centroid, which are then often even simply averaged to obtain a single crisp output. Many successful applications of type-2 have been in control contexts, often focussing on reducing the RMSE. This is not taking full advantage of the extra modelling capabilities inherent in type-2 fuzzy sets. In this talk, I will present some of the current research being carried out within the LUCID group at Nottingham, and wider, into type-2 for modelling human reasoning. I will cover approaches and methodologies which make more use of type-2 capabilities, illustrating these with reference to practical applications such as classification of breast cancer tumours, modelling expert variability in cyber-security contexts, and other decision support problems.



Using Ontologies to Deploy Work Flows: An Approach to Clinical Guideline Execution

Paulo Novais
Universidade do Minho

Brief Bio
Paulo Novais is an Associate Professor with Habilitation of Computer Science at the Department of Informatics, in the School of Engineering of the University of Minho (Portugal) and a researcher at the ALGORITMI Centre in which he is the coordinator of the research group ISlab - Synthetic Intelligence, and the coordinator of the research line in “Ambient intelligence for well-being and Health Applications”.
He is the director of the PhD Program in Informatics and co-founder and Deputy Director of the Master in Law and Informatics at the University of Minho.
He started his career developing scientific research in the field of Intelligent Systems/Artificial Intelligence (AI), namely in Knowledge Representation and Reasoning, Machine Learning and Multi-Agent Systems.
His interest, in the last years, was absorbed by the different, yet closely related, concepts of Ambient Intelligence, Ambient Assisted Living, Intelligent Environments, Behavioural Analysis, Conflict Resolution and the incorporation of AI methods and techniques in these fields.
His main research aim is to make systems a little more smart, intelligent and also reliable.
He has led and participated in several research projects sponsored by Portuguese and European public and private Institutions and has supervised several PhD and MSc students. He is the co-author of over 250 book chapters, journal papers, conference and workshop papers and books.
He is the president of APPIA (the Portuguese Association for Artificial Intelligence) for 2016/2017, Portuguese representative at the IFIP - TC 12 - Artificial Intelligence chair of the Working Group on Intelligent Agent (WG12.3), and member of the executive committee of the IBERAMIA (IberoAmerican Society of Artificial Intelligence).
During the last years he has served as an expert/reviewer of several institutions such as EU Commission and FCT (Portuguese agency that supports science, technology and innovation).


Ontologies, as formal representations of the domain, capture the meaning of concepts in a domain and the relationships between them. Currently, many fields are harnessing the power of ontologies to enhance computational systems that perform sensitive tasks, to make them exchange information in a more efficient way and convey outputs in a more understandable manner. One of such fields is that of health care, particularly when it comes to Clinical Decision Support Systems. The deployment of Clinical Practice Guidelines in computational systems for clinical decision support has the potential to positively impact health care. However, current approaches to Computer-Interpretable Guidelines evidence a set of issues that leave them wanting. These issues are related with the lack of expressiveness of their underlying models, the complexity of knowledge acquisition with their tools, the absence of support to the clinical decision-making process, and the style of communication of Clinical Decision Support Systems implementing Computer-Interpretable Guidelines. Such issues pose as obstacles that prevent these systems from showing properties like modularity, flexibility, adaptability, and interactivity. All these properties reflect the concept of living guidelines. The CompGuide Framework for the development and deployment of Computer-Interpretable Guidelines addresses these limitations by using ontologies to increase the flexibility, adaptability and intervention of Clinical Decision Support Systems.