Witschel, Hans Friedrich

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Witschel
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Hans Friedrich
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Witschel, Hans Friedrich

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2009 - 200912010 - 201922
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Enddatum: 2019 × Typ: 04B - Beitrag Konferenzschrift ×

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  • Vorschaubild nicht verfügbar
    Publikation
    Case model for the RoboInnoCase recommender system for cases of digital business transformation: structuring information for a case of digital change
    (SciTePress, 2019) Witschel, Hans Friedrich; Peter, Marco; Seiler, Laura; Parlar, Soyhan; Gatziu Grivas, Stella; Bernardino, Jorge; Salgado, Ana; Filipe, Joaquim [in: ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings]
    In this work, we develop a case model to structure cases of past digital transformations which act as input data for a recommender system. The purpose of that recommender is to act as an inspiration and support for new cases of digital transformation. To define the case model, case analyses, where 40 cases of past digital transformations are analysed and coded to determine relevant attributes and values, literature research and the particularities of the case for digital change, are used as a basis. The case model is evaluated by means of an experiment where two different scenarios are fed into a prototypical case-based recommender system and then matched, based on an entropically derived weighting system, with the case base that contains cases structured according to the case model. The results not only suggest that the case model’s functionality can be guaranteed, but that a good quality of the given recommendations is achieved by applying a case-based recommender system using the proposed case model. The results not only suggest that the case model’s functionality can be guaranteed, but that a good quality of the given recommendations is achieved by applying a case-based recommender system using the proposed case model.
    04B - Beitrag Konferenzschrift
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    Publikation
    Enhancing reflective practices within business management education: what kinds of e-learning scenarios can be designed?
    (ACM, 2019) Inglese, Terry; von Kutzschenbach, Michael; Witschel, Hans Friedrich [in: IC4E '19. 10th International Conference on E-Education, E-Business, E-Management and E-Learning]
    Contrary to the dominant appearance of the topic ‘digitalization,’ a majority of managers do not know what it means and how they can leverage the development of new technologies and disruptive innovations for their business. Furthermore, doing business is getting increasingly complex due to globalization and specialization. Thus, it looks like everybody is hyperactively looking for an external solution to their managerial challenges while, at the same time, managers seem to have lost their intuition for future direction and are unable to step back and think about intended and unintended consequences of the digital revolution. We, who provide business management education for future leaders, are concerned about this development and teach our students to appreciate the discomfort with the hard work of thinking and reflecting to learn from the insights about innovation, strategy and personal development to achieve improved leadership competence. In this paper, we will present our lessons learnt from asking students of a leadership class at an applied university to write a reflective journal for deep learning purpose.
    04B - Beitrag Konferenzschrift
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    Publikation
    Learning and engineering similarity functions for business recommenders
    (2019) Witschel, Hans Friedrich; Martin, Andreas; Martin, Andreas; Hinkelmann, Knut; Gerber, Aurona; Lenat, Doug; Harmelen, Frank van; Clark, Peter [in: Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019)]
    We study the optimisation of similarity measures in tasks where the computation of similarities is not directly visible to end users, namely clustering and case-based recommenders. In both, similarity plays a crucial role, but there are also other algorithmic components that contribute to the end result. Our suggested approach introduces a new form of interaction into these scenarios that make the use of similarities transparent to end users and thus allows to gather direct feedback about similarity from them. This happens without distracting them from their goal – rather allowing them to obtain better and more trustworthy results by excluding dissimilar items. We then propose to use the feedback in a way that incorporates machine learning for updating weights and decisions of knowledge engineers about possible additional features, based on insights derived from a summary of user feedback. The reviewed literature and our own previous empirical investigations suggest that this is the most feasible way – involving both machine and human, each in a task that they are particularly good at.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Enhance classroom preparation for flipped classroom using AI and analytics
    (SciTePress, 2018) Diwanji, Prajakta; Hinkelmann, Knut; Witschel, Hans Friedrich; Hammoudi, Slimane; Smialek, Michal; Camp, Olivier; Filipe, Joaquim [in: ICEIS 2018. 20th International Conference on Enterprise Information Systems. Proceedings]
    In a flipped classroom setting, it is important for students to come prepared for the classroom. Being prepared in advance helps students to grasp the concepts taught during classroom sessions. A recent student survey at Fachhochschule Nordwestschweiz (FHNW), Business School, Switzerland, revealed that only 27.7% students often prepared before a class and only 7% always prepared before a class. The main reason for not preparing for classes was lack of time and workload. A literature review study revealed that there is a growth of the use of Artificial Intelligence (AI), for example, chatbots and teaching assistants, which support both teachers and students for classroom preparation. There is also a rise in the use of data analytics to support tutor decision making in real time. However, many of these tools are based on external motivation factors like grading and assessment. Intrinsic motivation among students is more rewarding in the long term. This paper proposes an application based on AI and data analysis that focuses on intrinsically motivating and preparing students in a flipped classroom approach.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Training and re-using human experience: a recommender for more accurate cost estimates in project planning
    (SciTePress, 2018) Rudolf von Rohr, Christian; Witschel, Hans Friedrich; Martin, Andreas [in: IC3K 2018 - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management]
    In many industries, companies deliver customised solutions to their (business) customers within projects. Estimating the human effort involved in such projects is a difficult task and underestimating efforts can lead to non-billable hours, i.e. financial loss on the side of the solution provider. Previous work in this area has focused on automatic estimation of the cost of software projects and has largely ignored the interaction between automated estimation support and human project leads. Our main hypothesis is that an adequate design of such interaction will increase the acceptance of automatically derived estimates and that it will allow for a fruitful combination of data-driven insights and human experience. We therefore build a recommender that is applicable beyond software projects and that suggests job positions to be added to projects and estimated effort of such positions. The recommender is based on the analysis of similar cases (case-based reasoning), "explains" derived similarities and allows human intervention to manually adjust the outcomes. Our experiments show that recommendations were considered helpful and that the ability of the system to explain and adjust these recommendations was heavily used and increased the trust in the system. We conjecture that the interaction of project leads with the system will help to further improve the accuracy of recommendations and the support of human learning in the future.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Random walks on human knowledge: incorporating human knowledge into data-driven recommenders
    (2018) Witschel, Hans Friedrich; Martin, Andreas; Bernardino, Jorge; Salgado, Ana; Filipe, Joaquim [in: IC3K 2018. 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Proceedings]
    We explore the use of recommender systems in business scenarios such as consultancy. In these situations, apart from personal preferences of users, knowledge about objective business-driven criteria plays a role. We investigate strategies for representing and incorporating such knowledge into data-driven recommenders. As a baseline, we choose a robust and flexible paradigm that is based on a simple graph-based representation of past customer cases and choices, in combination with biased random walks. On a real data set from a business intelligence consultancy firm, we study how the incorporation of two important types of explicit human knowledge – namely taxonomic and associative knowledge – impacts the effectiveness of a data-driven recommender. Our results show no consistent improvement for taxonomic knowledge, but quite substantial and significant gains when using associative knowledge.
    04B - Beitrag Konferenzschrift
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    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
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    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
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    Publikation
    Ensuring Action: Identifying Unclear Actor Specifications in Textual Business Process Descriptions
    (Springer, 2016) Sanne, Ulf; Ferrari, Alessio; Gnesi, Stefania; Witschel, Hans Friedrich; Ana, Fred; Aveiro, David [in: Proceedings of the 8th International Conference on Knowledge Management and Information Sharing (KMIS), 2016]
    In many organisations, business process (BP) descriptions are available in the form of written procedures, or operational manuals. These documents are expressed in informal natural language, which is inherently open to different interpretations. Hence, the content of these documents might be incorrectly interpreted by those who have to put the process into practice. It is therefore important to identify language defects in written BP descriptions, to ensure that BPs are properly carried out. Among the potential defects, one of the most relevant for BPs is the absence of clear actors in action-related sentences. Indeed, an unclear actor might lead to a missing responsibility, and, in turn, to activities that are never performed. This paper aims at identifying unclear actors in BP descriptions expressed in natural language. To this end, we define an algorithm named ABIDE, which leverages rule-based natural language processing (NLP) techniques. We evaluate the algorithm on a manually annotated data-set of 20 real-world BP descriptions (1,029 sentences). ABIDE achieves a recall of 87%, and a precision of 56%. We consider these results promising. Improvements of the algorithm are also discussed in the paper.
    04B - Beitrag Konferenzschrift
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    Publikation
    A Graph-Based Recommender for Enhancing the Assortment of Web Shops
    (2015) Riesen, Kaspar; Witschel, Hans Friedrich; Galliè, Emidio [in: Proceedings of Workshop on Data Mining in Marketing DMM'2015]
    In this work, we consider a situation where multiple Providers (competitors) serve a common market, using a common infrastructure of sales channels. More speci cally, we focus on multiple web shops that are run by the same web shop platform provider. Our goal is to recommend new items to complement the assortment of a provider, based on user behaviour in the other shops of the same platform. For this new problem, we propose to capture information on how items sell together in a shared product co-occurrence graph. We then adapt known graph-based recommenders to the problem. Further criteria for ranking recommended items are derived as part of a case study conducted in the context of IT web shops. They are combined with the scores of the graph recommenders in a nal ranking function. We evaluate this function with data from our case study context and based on judgments of one shop owner. Our results show that a good ranking can be achieved, reflecting the needs of the shop owner.
    04B - Beitrag Konferenzschrift