Hinkelmann, Knut

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Knut
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Hinkelmann, Knut

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Gerade angezeigt 1 - 10 von 18
  • Publikation
    A new approach for teaching programming: model-based agile programming (MBAD)
    (ACM, 2023) Telesko, Rainer; Spahic, Maja; Hinkelmann, Knut; Pande, Charuta [in: ICIEI 2023. Proceedings of 2023 The 8th International Conference on Information and Education Innovations]
    Designing courses for introductory programming courses with a heterogeneous audience (business and IT background as well) is a challenging task. In an internal project of the School of Business at the FHNW University of Applied Sciences and Arts Northwestern Switzerland (FHNW) a group of lecturers developed a concept entitled “Model-based agile development” (MBAD) which supports the learning of elementary programming concepts in an agile environment and builds the basis for advanced courses. MBAD will be used as a basic learning module for various Bachelor programs at the FHNW.
    04B - Beitrag Konferenzschrift
  • Publikation
    Analysing barriers in the business ecosystem of European MaaS providers: an actor-network approach
    (2023) Gebhart, Julian; Schlick, Sandra; Marvell, Alan; Gerber, Aurona; Hinkelmann, Knut [in: Proceedings of Society 5.0 Conference 2023]
    As new Mobility as a Service (MaaS) platforms are being established in Europe, researchers and practitioners seek evidence on the barriers experienced by the MaaS providers in their evolving business ecosystem. This paper conceptualises the MaaS business ecosystem using a Systematic Literature Review (SLR) combined with Actor- Network Theory (ANT) by constructing an actor-network of key actors. This actor- network, along with the identified MaaS business ecosystem barriers, is then used for Multiple Case Study Research, interviewing 18 European MaaS experts. The cross-case analysis revealed how MaaS providers problematise, interest, enrol and mobilise their business ecosystems. Furthermore, the paper outlines and amends key barriers in the areas of (1) technology and data, (2) social and cultural, and (3) policy and regulation. Researchers and practitioners can use the findings of this study to formulate policies, create best practices or conduct further research on the development of MaaS.
    04B - Beitrag Konferenzschrift
  • Publikation
    Ontology-driven enhancement of process mining with domain knowledge
    (Sun SITE, Informatik V, RWTH Aachen, 2023) Eichele, Simon; Hinkelmann, Knut; Spahic, Maja; Martin, Andreas; Fill, Hans-Georg; Gerber, Aurona; Hinkelmann, Knut; Lenat, Doug; Stolle, Reinhard; Harmelen, Frank van [in: Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023)]
    Process mining is a technique used to analyze and understand business processes. It uses as input the event log, a type of data used to represent the sequence of activities occurring within a business process. An event log typically contains information such as the case ID, the performed activity’s name, the activity’s timestamp, and other data associated with the activity. By analyzing event logs, organizations can gain a deeper understanding of their business processes, identify areas for improvement, and make data-driven decisions to optimize their operations. However, as the event logs contain data collected from different systems involved in the process, such as ERP, CRM, or WfMS systems, they often lack the necessary context and knowledge to analyze and fully comprehend business processes. By extending the event logs with domain knowledge, organizations can gain a more complete and accurate insight into their business processes and make more informed decisions about optimizing them. This paper presents an approach for enhancing process mining with domain knowledge preserved in domain-specific OWL ontologies. Event logs are typically stored in structured form in relational databases. This approach first converts the process data into an event log which is then mapped with ontology concepts. The ontology contains classes and individuals representing background knowledge of the domain, which supports the understanding of the data. A class for the specific activities forms the link between the event log and the ontology. In this manner, it is possible to map the domain knowledge to a particular case and activity. This allows to determine conditions that must be satisfied for executing tasks and to prune discovered process models if they are too complex. This approach is demonstrated using data from the student admission process at FHNW and has been implemented in Protégé.
    04B - Beitrag Konferenzschrift
  • Publikation
    Leading in society 5.0, The 5Co leadership concept
    (2023) Aeschbacher, Marc; Legena, Valeria; Gerber, Aurona; Hinkelmann, Knut [in: Proceedings of society 5.0 conference 2023]
    04B - Beitrag Konferenzschrift
  • Publikation
    A computational literature analysis of conversational AI research with a focus on the coaching domain
    (2022) Pande, Charuta; Fill, Hans-Georg; Hinkelmann, Knut; Hinkelmann, Knut; Gerber, Aurona [in: Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society]
    We conduct a computational analysis of the literature on Conversational AI. We identify the trend based on all publications until the year 2020. We then concentrate on the publications for the last five years between 2016 and 2020 to find out the top ten venues and top three journals where research on Conversational AI has been published. Further, using the Latent Dirichlet Allocation (LDA) topic modeling technique, we discover nine important topics discussed in Conversational AI literature and specifically two topics related to the area of coaching. Finally, we detect the key authors who have contributed significantly to Conversational AI research and area(s) related to coaching. We determine the key authors' areas of expertise and how the knowledge is distributed across different regions. Our findings show an increasing trend and thus, an interest in Conversational AI research, predominantly from the authors in Europe.
    04B - Beitrag Konferenzschrift
  • Publikation
    Sustainability orientation in business models of Swiss start-ups
    (2021) Milow, Uta; Gerber, Aurona; Hinkelmann, Knut [in: Proceedings of Society 5.0 Conference 2021]
    Research on Sustainable Business Models of start-ups currently focuses on those which pursue a sustainability goal as a main aspect and at least also follow an ethical motivation, possibly in addition to the profit motive. This paper aims to firstly identify useful criteria for describing sustainability in business models and secondly does an investigation on the sustainability orientation and implementation in business models of participating start-ups in the Swiss Innovation Challenge, a business plan competition. As sustainability was no criterion in the application process, many of the start-ups didn’t have a strong sustainability orientation. It will be examined to what extent these start-ups take sustainability aspects into account, and which ones in detail. Secondly, it is examined which business model types are used here in order to identify prevailing types and patterns for start-ups that are not selected for their sustainability orientation. The 25 start-up teams were interviewed with a semi-structured interview guide, including an evaluations of sustainability criteria. Almost all start-ups have a strong profit orientation and many also consider sustainability in their business model, though mostly with only one field of action. The linear business model is dominant and only few start-ups contribute to the circular economy. Another outcome of the survey is that the sustainable business model patterns should be adapted for this target group of start-ups not geared towards sustainability for future research.
    04B - Beitrag Konferenzschrift
  • Publikation
    Challenges of implementing zero waste strategies in the gastronomy industry
    (2021) Daub, Claus-Heinrich; Gerhard, Carole; Altermatt, Monisser; Gerber, Aurona; Hinkelmann, Knut [in: Proceedings of the first international conference on society 5.0]
    This case tells the story of the Café spurlos which aims at becoming a zero waste business and thus making a significant contribution to combating one of the greatest challenges facing society today: the transformation of the eco-nomic system into a circular economy. Besides the COVID-crisis and the thereof resulting issues, the café also faces challenges related to its vision of incorporat-ing the zero waste philosophy in its concept. The case explores the complexity of zero waste, analyses further hurdles for zero waste endeavors in the gastronomy industry and illustrates the constant balancing act of social businesses between staying true to one’s mission and catering to the needs, wants and expectations of the market.
    04B - Beitrag Konferenzschrift
  • Publikation
    Hybrid conversational AI for intelligent tutoring systems
    (Sun SITE, Informatik V, RWTH Aachen, 2021) Pande, Charuta; Witschel, Hans Friedrich; Martin, Andreas; Montecchiari, Devid; Martin, Andreas; Hinkelmann, Knut; Fill, Hans-Georg; Gerber, Aurona; Lenat, Dough; Stolle, Reinhard; Harmelen, Frank van [in: Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021)]
    We present an approach to improve individual and self-regulated learning in group assignments. We focus on supporting individual reflection by providing feedback through a conversational system. Our approach leverages machine learning techniques to recognize concepts in student utterances and combines them with knowledge representation to infer the student’s understanding of an assignment’s cognitive requirements. The conversational agent conducts end-to-end conversations with the students and prompts them to reflect and improve their understanding of an assignment. The conversational agent not only triggers reflection but also encourages explanations for partial solutions.
    04B - Beitrag Konferenzschrift
  • Publikation
    Decision support combining machine learning, knowledge representation and case-based reasoning
    (Sun SITE, Informatik V, RWTH Aachen, 2021) Mehli, Carlo; Hinkelmann, Knut; Jüngling, Stephan [in: Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021)]
    Knowledge and knowledge work are essential for the success of companies nowadays. Decisions are based on knowledge and better knowledge leads to more informed decisions. Therefore, the management of knowledge and support of decision making has increasingly become a source of competitive advantage for organizations. The current research uses a design science research approach (DSR) with the aim to improve the decision making of a knowledge intensive process such as the student admission process, which is done manually until now. In the awareness phase of the DSR process, the case study research method is applied to analyze the decision making and the knowledge that is needed to derive the decisions. Based on the analysis of the application scenario, suitable methods to support decision making were identified. The resulting system design is based on a combination of Case-Based Reasoning (CBR) and Machine Learning (ML). The proposed system design and prototype has been validated using triangulation evaluation, to assess the impact of the proposed system on the application scenario. The evaluation revealed that the additional hints from CBR and ML can assist the deans of the study program to improve the knowledge management and increase the quality, transparency and consistency of the decision-making process in the student application process. Furthermore, the proposed approach fosters the exchange of knowledge among the different process participants involved and codifies previously tacit knowledge to some extent and provides relevant externalized knowledge to decision makers at the required moment. The designed prototype showcases how ML and CBR methodologies can be combined to support decision making in knowledge intensive processes and finally concludes with potential recommendations for future research.
    04B - Beitrag Konferenzschrift
  • Publikation
    Towards AI-based solutions in the system development lifecycle
    (2020) Jüngling, Stephan; Peraic, Martin; Martin, Andreas; Martin, Andreas; Hinkelmann, Knut; Fill, Hans-Georg; Gerber, Aurona; Lenat, Doug; Stolle, Reinhard; van Harmelen, Frank [in: Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice (AAAI-MAKE 2020)]
    Many teams across different industries and organizations explicitly apply agile methodologies such as Scrum in their system development lifecycle (SDLC). The choice of the technology stack, the programming language, or the decision whether AI solutions could be incorporated into the system design either is given by corporate guidelines or is chosen by the project team based on their individual skill set. The paper describes the business case of implementing an AI-based automatic passenger counting system for public transportation, shows preliminary results of the prototype using anonymous passenger recognition on the edge with the help of Google Coral devices.It shows how different solutions could be integrated with the help of rule base systems and how AI-based solutions could be established in the SDLC as valid and cost-saving alternatives to traditionally programmed software components.
    04B - Beitrag Konferenzschrift