Hinkelmann, Knut

Lade...
Profilbild
E-Mail-Adresse
Geburtsdatum
Projekt
Organisationseinheiten
Berufsbeschreibung
Nachname
Hinkelmann
Vorname
Knut
Name
Hinkelmann, Knut

Suchergebnisse

Gerade angezeigt 1 - 10 von 23
  • Publikation
    A new approach for teaching programming: model-based agile programming (MBAD)
    (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
    Ontology-driven enhancement of process mining with domain knowledge
    (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
    Hybrid conversational AI for intelligent tutoring systems
    (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
    (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
    Der Geschäftsprozess in der Cloud
    (Swiss Professional Media, 2018) Hinkelmann, Knut; Woitsch, Robert [in: Unternehmer Zeitung]
    CLOUD-COMPUTING: Zunehmend durchdringt die IT auch das Geschäftsmodell. Für die Strategie in der Cloud wurde im Rahmen eines EU-Projekts ein neues Konzept erarbeitet.
    01B - Beitrag in Magazin oder Zeitung
  • Publikation
    Run-Time Planning of Case-based Business Processes
    (IEEE, 2016) Hinkelmann, Knut; Sprovieri, Danillo; Diaz, Daniel; Mazo, Raul; Espana, Sergio; Ralyte, Jolita; Souveyet, Carine [in: IEEE Tenth International Conference on Research Challenges in Information Science]
    Organizations act in highly competitive markets, which forces them to be flexible. Constantly changing business requirements require flexible business processes. Case Management Model and Notation (CMMN) supports modeling run-time flexibility of partially structured business process models, but does not fully specify the control flow. Objective: The goal is to develop a planning algorithm that supports the case worker in planning case-based business processes at run-time. Method: We identify the requirements of run-time planning of partly structured processes by analyzing the admission process for the master degree at FHNW. To plan the process instance, we develop a planning algorithm. Our planning algorithm is evaluated using concrete cases provided by FHNW in order to demonstrate real application. Results: The planning algorithm reflects the requirements for serializing tasks at run-time. Conclusion: Our planning algorithm allows to automatically deriving context-specific execution plans for CMMN models at run-time.
    04 - Beitrag Sammelband oder Konferenzschrift
  • Publikation
    Business Process as a Service (BPaaS): The Smart BPaaS Design Environment
    (2016) Woitsch, Robert; Hinkelmann, Knut; Juan Ferrer, Ana Maria; Yuste, Joaquin Iranzo; Karagiannis, Dimitris; Schlamberger, Niko [in: CAiSE 2016 Industry Track]
    This paper introduces the project idea of Business Processes as a Services (BPaaS) that is worked out in the H2020 project CloudSocket. Concept models and semantics are used to align domain specific business processes with executable workflows that are deployed and in production in a multi-cloud environment. The Business Process Management System Paradigm (BPMS) is requesting the functional capabilities of the so-called BPaaS Environments (i) design, (ii) allocation, (iii) execution and (iv) evaluation, which technically compose the CloudSocket Broker platform. This paper introduces first findings of aligning customers’ business needs with BPaaS cloud offerings using a model-based approach.
    04 - Beitrag Sammelband oder Konferenzschrift
  • Publikation
    Workplace Learning - Providing Recommendations of Experts and Learning Resources in a Context-sensitive and Personalized Manner
    (2016) Emmenegger, Sandro; Laurenzi, Emanuele; Thönssen, Barbara; Zhang Sprenger, Congyu; Hinkelmann, Knut; Witschel, Hans Friedrich [in: Proceedings of Special Session on Learning Modeling in Complex Organizations (LCMO) at MODELSWARD'16]
    Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize user s' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.
    04B - Beitrag Konferenzschrift
  • Publikation
    KPIs 4 Workplace Learning
    (Springer, 2016) Emmenegger, Sandro; Thönssen, Barbara; Hinkelmann, Knut; Witschel, Hans Friedrich; Ana, Fred; Aveiro, David [in: Proceedings of the 8th International Conference on Knowledge Management and Information Sharing (KMIS)]
    Enterprises and Public Administrations alike need to ensure that newly hired employees are able to learn the ropes fast. Employers also need to support continuous workplace learning. Work-place learning should be strongly related to business goals and thus, learning goals should direct-ly add to business goals. To measure achievement of both learning and business goals we pro-pose augmented Key Performance Indicators (KPI). In our research we applied model driven engineering. Hence we developed a model for a Learning Scorecard comprising of business and learning goals and their KPIs represented in an ontology. KPI performance values and scores are calculated with formal rules based on the SPARQL Inferencing Notation. Results are presented in a dashboard on an individual level as well as on a team/group level. Requirements, goals and KPIs as well as performance measurement were defined in close co-operation with Marche Region, business partner in Learn PAd.
    04B - Beitrag Konferenzschrift
  • Publikation
    A new paradigm for the continuous alignment of business and IT: combining enterprise architecture modelling and enterprise ontology
    (Elsevier, 2016) Hinkelmann, Knut; Gerber, Aurona; Karagiannis, Dimitris; Thönssen, Barbara; van der Merwe, Alta; Woitsch, Robert [in: Computers in Industry]
    The paper deals with Next Generation Enterprise Information Systems in the context of Enterprise Engineering. The continuous alignment of business and IT in a rapidly changing environment is a grand challenge for today’s enterprises. The ability to react timeously to continuous and unexpected change is called agility and is an essential quality of the modern enterprise. Being agile has consequences for the engineering of enterprises and enterprise information systems. In this paper a new paradigm for next generation enterprise information systems is proposed, which shifts the development approach of model-driven engineering to continuous alignment of business and IT for the agile enterprise. It is based on a metamodelling approach, which supports both human-interpretable graphical enterprise architecture and machine-interpretable enterprise ontologies. Furthermore, next generation enterprise information systems are described, which embed modelling tools and algorithms for model analysis.
    01A - Beitrag in wissenschaftlicher Zeitschrift