Witschel, Hans Friedrich
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Hans Friedrich
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Witschel, Hans Friedrich
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- PublikationLearning 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
- PublikationDetermining information relevance based on personalization techniques to meet specific user needs(Springer, 2018) Thönssen, Barbara; Witschel, Hans Friedrich; Rusinov, Oleg; Dornberger, Rolf [in: Business information systems and technology 4.0 - New trends in the age of digital change]04A - Beitrag Sammelband
- PublikationImproving the quality of business process descriptions of public administrations: resources and research challenges(Emerald, 2018) Ferrari, Alessio; Witschel, Hans Friedrich; Spagnolo, Giorgio Oronzo; Gnesi, Stefania [in: Business Process Management Journal]01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationBusiness Analytics aus der Cloud: Möglichkeiten und Herausforderungen(2017) Gatziu Grivas, Stella; Witschel, Hans Friedrich; Peter, Marc K. [in: KMU-Transformation - Als KMU die Digitale Transformation erfolgreich umsetzen]04 - Beitrag Sammelband oder Konferenzschrift
- PublikationWorkplace 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
- PublikationKPIs 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
- PublikationEnsuring 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
- PublikationA 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
- PublikationAdapting an Enterprise Architecture for Business Intelligence(2015) von Bergen, Pascal; Hinkelmann, Knut; Witschel, Hans Friedrich [in: 8th IFIP WG 8.1 working conference on the Practice of Enterprise Modelling]04B - Beitrag Konferenzschrift
- PublikationUsing consumer behavior data to reduce energy consumption in smart homes(2015) Schweizer, Daniel; Zehnder, Michael; Wache, Holger; Zanatta, Danilo; Rodriguez, Miguel; Witschel, Hans Friedrich [in: Proceedings of the IEEE 2015 International Conference on Machine Learning and Applications]This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life smart home event data. The performance of the proposed algorithm is compared to existing algorithms regarding completeness/correctness of the results, run times as well as memory consumption and elaborates on the shortcomings of the different solutions.04B - Beitrag Konferenzschrift
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