Witschel, Hans Friedrich

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Hans Friedrich
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Witschel, Hans Friedrich

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Publikation

New hybrid techniques for business recommender systems

2022, Pande, Charuta, Witschel, Hans Friedrich, Martin, Andreas

Besides the typical applications of recommender systems in B2C scenarios such as movie or shopping platforms, there is a rising interest in transforming the human-driven advice provided, e.g., in consultancy via the use of recommender systems. We explore the special characteristics of such knowledge-based B2B services and propose a process that allows incorporating recommender systems into them. We suggest and compare several recommender techniques that allow incorporating the necessary contextual knowledge (e.g., company demographics). These techniques are evaluated in isolation on a test set of business intelligence consultancy cases. We then identify the respective strengths of the different techniques and propose a new hybridisation strategy to combine these strengths. Our results show that the hybridisation leads to substantial performance improvement over the individual methods.

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Publikation

Visualization of patterns for hybrid learning and reasoning with human involvement

2020, Witschel, Hans Friedrich, Pande, Charuta, Martin, Andreas, Laurenzi, Emanuele, Hinkelmann, Knut, Dornberger, Rolf

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Case model for the RoboInnoCase recommender system for cases of digital business transformation: structuring information for a case of digital change

2019, Witschel, Hans Friedrich, Peter, Marco, Seiler, Laura, Parlar, Soyhan, Gatziu Grivas, Stella, Bernardino, Jorge, Salgado, Ana, Filipe, Joaquim

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.

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Enhance classroom preparation for flipped classroom using AI and analytics

2018, Diwanji, Prajakta, Hinkelmann, Knut, Witschel, Hans Friedrich, Hammoudi, Slimane, Smialek, Michal, Camp, Olivier, Filipe, Joaquim

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.

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Publikation

Natural language-based user guidance for knowledge graph exploration: a user study

2021, Witschel, Hans Friedrich, Riesen, Kaspar, Grether, Loris, Cucchiara, Rita, Fred, Ana, Filipe, Joaquim

Large knowledge graphs hold the promise of helping knowledge workers in their tasks by answering simple and complex questions in specialised domains. However, searching and exploring knowledge graphs in current practice still requires knowledge of certain query languages such as SPARQL or Cypher, which many untrained end users do not possess. Approaches for more user-friendly exploration have been proposed and range from natural language querying over visual cues up to query-by-example mechanisms, often enhanced with recommendation mechanisms offering guidance. We observe, however, a lack of user studies indicating which of these approaches lead to a better user experience and optimal exploration outcomes. In this work, we make a step towards closing this gap by conducting a qualitative user study with a system that relies on formulating queries in natural language and providing answers in the form of subgraph visualisations. Our system is able to offer guidance via query recommendations based on a current context. The user study evaluates the impact of this guidance in terms of both efficiency and effectiveness (recall) of user sessions. We find that both aspects are improved, especially since query recommendations provide inspiration, leading to a larger number of insights discovered in roughly the same time.

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A dialog-based tutoring system for project-based learning in information systems education

2020, Witschel, Hans Friedrich, Diwanji, Prajakta, Hinkelmann, Knut, Dornberger, Rolf

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Enhancing reflective practices within business management education: what kinds of e-learning scenarios can be designed?

2019, Inglese, Terry, von Kutzschenbach, Michael, Witschel, Hans Friedrich

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.

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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

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.

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Publikation

KvGR: A graph-based interface for explorative sequential question answering on heterogeneous information sources

2020, Witschel, Hans Friedrich, Riesen, Kaspar, Grether, Loris, Jose, Joemon M., Yilmaz, Emine, Magalhães, João, Castells, Pablo, Ferro, Nicola, Silva, Mário J., Martins, Flávio

Exploring a knowledge base is often an iterative process: initially vague information needs are refined by interaction. We propose a novel approach for such interaction that supports sequential question answering (SQA) on knowledge graphs. As opposed to previous work, we focus on exploratory settings, which we support with a visual representation of graph structures, helping users to better understand relationships. In addition, our approach keeps track of context – an important challenge in SQA – by allowing users to make their focus explicit via subgraph selection. Our results show that the interaction principle is either understood immediately or picked up very quickly – and that the possibility of exploring the information space iteratively is appreciated.

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Publikation

Determining information relevance based on personalization techniques to meet specific user needs

2018, Thönssen, Barbara, Witschel, Hans Friedrich, Rusinov, Oleg, Dornberger, Rolf