Machine Learning and Knowledge Extraction: 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual ... (Lecture Notes in Computer Science, 12844)

366 Pages·2021·36.163 MB·English

by  Andreas Holzinger (editor), Peter Kieseberg (editor), A Min Tjoa (editor), Edgar Weippl (editor)

Andreas Holzinger
Peter Kieseberg
A Min Tjoa
Edgar Weippl (Eds.)
4
4
8
2 Machine Learning
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and Knowledge Extraction
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5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9
International Cross-Domain Conference, CD-MAKE 2021
Virtual Event, August 17–20, 2021
Proceedings
Lecture Notes in Computer Science 12844
Founding Editors
Gerhard Goos
Karlsruhe Institute of Technology, Karlsruhe, Germany
Juris Hartmanis
Cornell University, Ithaca, NY, USA
Editorial Board Members
Elisa Bertino
Purdue University, West Lafayette, IN, USA
Wen Gao
Peking University, Beijing, China
Bernhard Steffen
TU Dortmund University, Dortmund, Germany
Gerhard Woeginger
RWTH Aachen, Aachen, Germany
Moti Yung
Columbia University, New York, NY, USA
More information about this subseries at http://www.springer.com/series/7409
Andreas Holzinger Peter Kieseberg
(cid:129) (cid:129)
A Min Tjoa Edgar Weippl (Eds.)
(cid:129)
Machine Learning
and Knowledge Extraction
5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9
International Cross-Domain Conference, CD-MAKE 2021
–
Virtual Event, August 17 20, 2021
Proceedings
123
Editors
Andreas Holzinger PeterKieseberg
Institute for Medical Informatics, Statistics St.PöltenUniversity ofApplied Sciences
andDocumentation andInstitute for St.Pölten,Austria
Information Systems andComputer Media
Edgar Weippl
Medical University Graz andGraz
SBAResearch
University of Technology
Vienna,Austria
Graz,Austria
Research Group Security andPrivacy
xAILab, AlbertaMachineIntelligence
University of Vienna
Institute
Vienna,Austria
University of Alberta
Edmonton, AB,Canada
AMin Tjoa
Institute of Software Technology
andInteractive Systems
Technische UniversitätWien
Vienna,Austria
ISSN 0302-9743 ISSN 1611-3349 (electronic)
Lecture Notesin Computer Science
ISBN 978-3-030-84059-4 ISBN978-3-030-84060-0 (eBook)
https://doi.org/10.1007/978-3-030-84060-0
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Preface
The International Cross Domain Conference for Machine Learning & Knowledge
Extraction (CD-MAKE) is a joint effort of IFIP TC 5, IFIP TC 12, IFIP WG 8.4,
IFIP WG 8.9, and IFIP WG 12.9 and is held in conjunction with the International
Conference on Availability, Reliability, and Security (ARES). This fifth installment
was organized virtually by SBA Research due to the ongoing COVID-19 pandemic,
and took place during August 17–20, 2021.
ThelettersCDinCD-MAKEstandfor“Cross-Domain”anddescribetheintegration
and appraisal of different fields and application domains to provide an atmosphere to
foster different perspectives and opinions. The conference fosters an integrative
machine learning approach, considering the importance of data science and visual-
izationforthealgorithmicpipelinewithastrongemphasisonprivacy,dataprotection,
safety,andsecurity.Itisdedicatedtoofferinganinternationalplatformfornovelideas
and a fresh look on methodologies to put crazy ideas into business for the benefit of
humans. Serendipity is a desired effect, which may lead to the cross-fertilization of
methodologies and the transfer of algorithmic developments.
The acronym MAKE stands for “MAchine Learning & Knowledge Extraction”, a
field of artificial intelligence (AI) that, while quite old in its fundamentals, has just
recentlybeguntothrivebasedonbothnoveldevelopmentsinthealgorithmicareaand
the availability of vast computing resources at a comparatively low cost.
Machine learning (ML) studies algorithms that can learn from data to gain
knowledgefromexperienceandtogeneratedecisionsandpredictions.Agrandgoalis
in understanding intelligence for the design and development of algorithms that work
autonomously (ideally without a human-in-the-loop) and can improve their learning
behavior over time. The challenge is to discover relevant structural and/or temporal
patterns (“knowledge”) in data, which is often hidden in arbitrarily high dimensional
spaces, and thus simply not accessible to humans. Knowledge extraction is one of the
oldest fields in AI and is seeing a renaissance, particularly in the combination of
statistical methods with classical ontological approaches. AI is currently undergoing a
kindofCambrianexplosionandisthefastest-growingfieldincomputersciencetoday
thanks to the usable successes in machine learning. There are many application
domains, e.g., in medicine, etc., with many use cases from our daily lives, e.g., rec-
ommendersystems,speechrecognition,autonomousdriving,etc.Thegrandchallenges
lie in sensemaking, in context understanding, and in decision-making under uncer-
tainty, as well as solving the problem of explainability. Our real world is full of
uncertainties and probabilistic inference enormously influences AI generally and ML
specifically. The inverse probability allows us to infer unknowns, to learn from data,
and to make predictions to support decision-making. Whether in social networks,
recommender systems, health applications, or industrial applications, the increasingly
complexdatasetsrequireajointinterdisciplinaryeffortinvolvingthehuman-in-control
vi Preface
to foster a better understanding of the ethical and social issues accountability,
retractability, explainability, causability, and privacy, safety and security!
A few words about IFIP: IFIP – the International Federation for Information Pro-
cessing—is the leading multi-national, non-governmental, apolitical organization in
informationand communications technologies and computer sciences; it isrecognized
by the United Nations (UN) and was established in 1960 under the auspices of the
UNESCO as an outcome of the first World Computer Congress held in Paris in 1959.
IFIP is incorporated in Austria by decree of the Austrian Foreign Ministry
(September 20, 1996, GZ 1055.170/120-I.2/96) granting IFIP the legal status of a
non-governmental international organization under the Austrian Law on the Granting
of Privileges to Non-Governmental International Organizations (Federal Law Gazette
1992/174). IFIP brings together more than 3500 scientists without boundaries from
both academia and industry, organized in more than 100 Working Groups (WGs) and
13 Technical Committees (TCs).
To acknowledge all those who also contributed to the organizational effort and
stimulatingdiscussionsatCD-MAKE2021wouldbeimpossibleinaprefacelikethis.
Many people also contributed to the development of this volume, either directly or
indirectly, so, again, it would be impossible to list all of them. We herewith thank all
local, national, and international colleagues and friends for their positive and sup-
portive encouragement. Finally, yet importantly, we thank the Springer management
team and the Springer production team for their professional support.
Thank you to all! Let’s MAKE it!
June 2021 Andreas Holzinger
Peter Kieseberg
Edgar Weippl
A Min Tjoa
Organization
Conference Organizers
Andreas Holzinger Medical University of Graz and Graz University
of Technology, Austria, and University of Alberta,
Canada
Peter Kieseberg FH St.Pölten, Austria
Edgar Weippl SBA Research and University of Vienna, Austria
A Min Tjoa TU Vienna, Austria
Program Committee
Frantisek Babic Technical University of Košice, Slovakia
Smaranda Belciug University of Craiova, Romania
Elisa Bertino Purdue University, USA
Chris Biemann Universität Hamburg, Germany
Jiang Bian University of Florida, USA
Malin Bradley Vanderbilt University, USA
Ivan Bratko University of Ljubljana, Slovenia
Guido Bologna Université de Genève, Switzerland
Francesco Buccafurri Universita Mediterranea di Reggio Calabria, Italy
Federico Cabitza University of Milano-Bicocca, Italy
Andre Calero-Valdez RWTH Aachen University, Germany
Andrea Campagner University of Milano-Bicocca, Italy
Angelo Cangelosi University of Manchester, UK
Mirko Cesarini University of Milano-Bicocca, Milan, Italy
Krzysztof J. Cios Virginia Commonwealth University, USA
Carlo Combi University of Verona, Italy
Beatriz De La Iglesia University of East Anglia, UK
Gloria Cerasela Crisan Vasile Alecsandri University of Bacau, Romania
Alexiei Dingli University of Malta, Malta
Josep Domingo-Ferrer Universitat Rovira i Virgili, Spain
Isao Echizen National Institute of Informatics, Japan
Massimo Ferri University of Bologna, Italy
Ulrich Furbach University of Koblenz, Germany
Hugo Gamboa PLUX Wireless Biosensors and Universidade Nova de
Lisboa, Portugal
Barbara Hammer University of Bielefeld, Germany
Pitoyo Hartono Chukyo University, Japan
Barna Laszlo Iantovics “George Emil Palade” University of Medicine,
Pharmacy, Sciences and Technology of Targu
Mures, Romania
viii Organization
Epaminodas Kapetanios University of Westminster, UK
Andreas Kerren Linköping University and Linnaeus University,
Sweden
Robert Laramee University of Nottingham, UK
Max Little University of Birmingham, UK
Luca Longo Technological University Dublin, Ireland
Ljiljana Majnaric-Trtica University of Osijek, Croatia
Donato Malerba Università degli Studi di Bari Aldo Moro, Italy
Fabio Mercorio University of Milano-Bicocca, Italy
Yoan Miche Nokia Bell Labs, Finland
Paolo Mignone Università degli Studi di Bari Aldo Moro, Italy
Vasile Palade Coventry University, UK
Jan Paralic Technical University of Kosice, Slovakia
Camelia-M. Pintea Technical University of Cluj-Napoca, Romania
Luca Romeo UniversitàPolitecnicadelleMarcheandIstitutoItaliano
di Tecnologia, Italy
Pierangela Samarati Università degli Sudi di Milano, Italy
Andrzej Skowron Systems Research Institute, Polish Academy
of Sciences, and University of Warsaw, Poland
Dominik Slezak University of Warsaw, Poland
Hung Son Nguyen University of Warsaw, Poland
Irena Spasic Cardiff University, UK
Ivan Štajduhar University of Rijeka, Croatia
Catalin Stoean University of Craiova, Romania
Bharath Sudharsan National University of Ireland Galway, Ireland
A Min Tjoa TU Wien, Austria
Dimitar Trajanov Ss. Cyril and Methodius University in Skopje,
Macedonia
Marco Tulio Ribeiro University of Washington, USA
Jean Vanderdonckt Université catholique de Louvain, Belgium
Markus Wagner University of Applied Sciences St. Pölten, Austria
Edgar Weippl SBA Research and University of Vienna, Austria
Kai Xu Middlesex University London, UK
Pinar Yildirim Okan University, Turkey
Jianlong Zhou University of Technology Sydney, Australia
Contents
Digital Transformation for Sustainable Development Goals (SDGs) -
A Security, Safety and Privacy Perspective on AI. . . . . . . . . . . . . . . . . . . . 1
Andreas Holzinger, Edgar Weippl, A Min Tjoa, and Peter Kieseberg
WheninDoubt,Ask:GeneratingAnswerableandUnanswerableQuestions,
Unsupervised . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Liubov Nikolenko and Pouya Rezazadeh Kalehbasti
Self-propagating Malware Containment via Reinforcement Learning . . . . . . . 35
Sebastian Eresheim and Daniel Pasterk
Text2PyCode: Machine Translation of Natural Language Intent to Python
Source Code. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Sridevi Bonthu, S. Rama Sree, and M. H. M. Krishna Prasad
Automated Short Answer Grading Using Deep Learning: A Survey . . . . . . . 61
Sridevi Bonthu, S. Rama Sree, and M. H. M. Krishna Prasad
Fair and Adequate Explanations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Nicholas Asher, Soumya Paul, and Chris Russell
Mining Causal Hypotheses in Categorical Time Series by Iterating
on Binary Correlations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Bora I. Kumova and Dirk Saller
Active Finite Reward Automaton Inference and Reinforcement Learning
Using Queries and Counterexamples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Zhe Xu, Bo Wu, Aditya Ojha, Daniel Neider, and Ufuk Topcu
Rice Seed Image-to-Image Translation Using Generative Adversarial
Networks to Improve Weedy Rice Image Classification. . . . . . . . . . . . . . . . 137
Atthakorn Petchsod and Tanasai Sucontphunt
Reliable AI Through SVDD and Rule Extraction . . . . . . . . . . . . . . . . . . . . 153
Alberto Carlevaro and Maurizio Mongelli
Airbnb Price Prediction Using Machine Learning and Sentiment Analysis . . . 173
Pouya Rezazadeh Kalehbasti, Liubov Nikolenko, and Hoormazd Rezaei
Towards Financial Sentiment Analysis in a South African Landscape . . . . . . 185
Michelle Terblanche and Vukosi Marivate