@inproceedings{29290, abstract = {{Classifying nodes in knowledge graphs is an important task, e.g., predicting missing types of entities, predicting which molecules cause cancer, or predicting which drugs are promising treatment candidates. While black-box models often achieve high predictive performance, they are only post-hoc and locally explainable and do not allow the learned model to be easily enriched with domain knowledge. Towards this end, learning description logic concepts from positive and negative examples has been proposed. However, learning such concepts often takes a long time and state-of-the-art approaches provide limited support for literal data values, although they are crucial for many applications. In this paper, we propose EvoLearner - an evolutionary approach to learn ALCQ(D), which is the attributive language with complement (ALC) paired with qualified cardinality restrictions (Q) and data properties (D). We contribute a novel initialization method for the initial population: starting from positive examples (nodes in the knowledge graph), we perform biased random walks and translate them to description logic concepts. Moreover, we improve support for data properties by maximizing information gain when deciding where to split the data. We show that our approach significantly outperforms the state of the art on the benchmarking framework SML-Bench for structured machine learning. Our ablation study confirms that this is due to our novel initialization method and support for data properties.}}, author = {{Heindorf, Stefan and Blübaum, Lukas and Düsterhus, Nick and Werner, Till and Golani, Varun Nandkumar and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{WWW}}, pages = {{818--828}}, publisher = {{ACM}}, title = {{{EvoLearner: Learning Description Logics with Evolutionary Algorithms}}}, doi = {{10.1145/3485447.3511925}}, year = {{2022}}, } @article{29851, author = {{Pestryakova, Svetlana and Vollmers, Daniel and Sherif, Mohamed and Heindorf, Stefan and Saleem, Muhammad and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}}, journal = {{Scientific Data}}, title = {{{CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications}}}, doi = {{10.1038/s41597-022-01298-2}}, year = {{2022}}, } @inbook{54310, author = {{Janus, Richard and Schroeter-Wittke, Harald}}, booktitle = {{Lust und Abgrund. Theologische und kulturwissenschaftliche Zugänge zum Begehren}}, editor = {{Janus, Richard and Schroeter-Wittke, Harald}}, pages = {{1--6}}, publisher = {{Springer Fachmedien Wiesbaden}}, title = {{{Einleitung}}}, year = {{2022}}, } @inbook{54309, author = {{Janus, Richard}}, booktitle = {{Lust und Abgrund. Theologische und kulturwissenschaftliche Zugänge zum Begehren}}, editor = {{Janus, Richard and Schroeter-Wittke, Harald}}, pages = {{53--67}}, publisher = {{Springer Fachmedien Wiesbaden}}, title = {{{Eingeständnis - Bekenntnis - Widerstand. Die Geste des Bekennens als Ende jeglichen Begehrens}}}, year = {{2022}}, } @inbook{54308, author = {{Janus, Richard}}, booktitle = {{Er ist unser Friede. Lesepredigten 1. Advent 2022 bis Pfingstmontag 2023. Textreihe V/1}}, editor = {{Schult, Maike}}, pages = {{249--254}}, publisher = {{Evangelischer Verlagsanstalt}}, title = {{{Pfingstmontag. Johannes 4, 19-26}}}, year = {{2022}}, } @book{54471, author = {{Mombeck, Mona Maria}}, isbn = {{978-3-658-37169-2}}, publisher = {{Springer}}, title = {{{Tiergestützte Pädagogik – Soziale Teilhabe – Inklusive Prozesse. Der Einsatz von Schulhunden aus wissenschaftlicher Perspektive}}}, year = {{2022}}, } @inproceedings{34674, abstract = {{Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation.}}, author = {{Sieger, Leonie Nora and Hermann, Julia and Schomäcker, Astrid and Heindorf, Stefan and Meske, Christian and Hey, Celine-Chiara and Doğangün, Ayşegül}}, booktitle = {{International Conference on Human-Agent Interaction}}, keywords = {{human-agent interaction, smart homes, supervised learning, participation}}, location = {{Christchurch, New Zealand}}, publisher = {{ACM}}, title = {{{User Involvement in Training Smart Home Agents}}}, doi = {{10.1145/3527188.3561914}}, year = {{2022}}, } @inproceedings{40054, author = {{Janicki, Nicole and Tenberge, Claudia}}, editor = {{Gill, David and Tuff, Jim and Kennedy, Thomas and Pendergast, Shawn and Jamil, Sana}}, location = {{St. John’s, Newfoundland and Labrador, Canada}}, pages = {{475--485}}, title = {{{Technology Education in Elementary School Using the Example of 'Learning Robots' – Development and Evaluation of an In-Service Teacher Training Concept.}}}, year = {{2022}}, } @misc{54537, author = {{Bauer, Maike and Hohwiller, Peter}}, booktitle = {{Der fremdsprachliche Unterricht Englisch}}, pages = {{30--33}}, title = {{{iMustHave. Anhand von Werbevideos den Kult um den digital global player Apple untersuchen}}}, volume = {{178}}, year = {{2022}}, } @misc{54534, author = {{Bauer, Maike and Menschig, Leigh}}, booktitle = {{Englisch Betrifft Uns}}, pages = {{1--5}}, title = {{{Should I Stay or Should I Go? Discussing the Advantages and Disadvantages of Taking a Gap Year}}}, volume = {{6}}, year = {{2022}}, } @misc{54535, author = {{Bauer, Maike and Menschig, Leigh}}, booktitle = {{Englisch Betrifft Uns}}, pages = {{22--25}}, title = {{{Virtual Employees in India: Off-site Employment for Large Corporations. Two oral exams}}}, volume = {{5}}, year = {{2022}}, } @misc{54536, author = {{Bauer, Maike and Menschig, Leigh}}, booktitle = {{Englisch Betrifft Uns}}, pages = {{17--21}}, title = {{{Modern Slavery vs. Fairtrade: Raising Awareness of the Working Conditions in India}}}, volume = {{5}}, year = {{2022}}, } @inproceedings{54541, author = {{Bauer, Maike}}, location = {{Münster}}, title = {{{Diaspora Short Stories – A Meaningful Aspect in Young Adult Literature? }}}, year = {{2022}}, } @inproceedings{52924, author = {{Tirtarasa, Satyadharma and Turhan, Anni-Yasmin}}, booktitle = {{SAC ’22: The 37th {ACM/SIGAPP} Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022}}, editor = {{Hong, Jiman and Bures, Miroslav and Park, Juw Won and Cerný, Tomás}}, pages = {{903–910}}, publisher = {{ACM}}, title = {{{Computing generalizations of temporal ϵL concepts with next and global}}}, doi = {{10.1145/3477314.3507136}}, year = {{2022}}, } @inproceedings{54549, author = {{Janicki, Nicole}}, location = {{Universität zu Köln}}, title = {{{Technische Bildung im Sachunterricht der Grundschule am Beispiel von Lernrobotern - Entwicklung und Evaluation eines Fortbildungskonzepts. Posterbeitrag im Rahmen der 31. Jahrestagung der Gesellschaft für Didaktik des Sachunterrichts (GDSU) vom 09. bis 12.03.2022 in Köln}}}, year = {{2022}}, } @article{52918, author = {{Baader, Franz and Koopmann, Patrick and Michel, Friedrich and Turhan, Anni-Yasmin and Zarrieß, Benjamin}}, journal = {{Theory Pract. Log. Program.}}, number = {{2}}, pages = {{162–192}}, title = {{{Efficient TBox Reasoning with Value Restrictions using the Flower Reasoner}}}, doi = {{10.1017/S1471068421000466}}, volume = {{22}}, year = {{2022}}, } @misc{54554, author = {{Janus, Richard}}, pages = {{1}}, publisher = {{Evangelischer Bund}}, title = {{{Gott wird Mensch. Weihnachten zwischen Fiktion und Evangelium}}}, volume = {{4}}, year = {{2022}}, } @article{49458, author = {{Nastjuk, I. and Trang, Simon Thanh-Nam and Papageorgiou, E.}}, journal = {{Electronic Markets}}, pages = {{1917--1924}}, title = {{{Smart cities and smart governance models for future cities}}}, volume = {{32}}, year = {{2022}}, } @article{49460, author = {{Masuch, K. and Greve, M. and Trang, Simon Thanh-Nam}}, journal = {{Electronic Markets}}, pages = {{829--848}}, title = {{{What to do after a data breach? Examining apology and compensation as response strategies for health service providers}}}, volume = {{31}}, year = {{2022}}, } @article{49459, author = {{Masuch, K. and Greve, M. and Trang, Simon Thanh-Nam}}, journal = {{Computers & Security}}, title = {{{Apologize or Justify? Examining the Impact of Data Breach Response Actions on Stock Value of Affected Companies}}}, volume = {{12}}, year = {{2022}}, }