TY - CHAP A1 - Drumm, Christian A1 - Lemcke, Jens A1 - Oberle, Daniel T1 - Integrating Semantic Web Services and Business Process Management: A Real Use Case T2 - Proceedings of the ESWC 2006 Workshop Semantics for Business Process Management 2006 (SBPM 2006), June 2006 Y1 - 2006 ER - TY - CHAP A1 - Kunfermann, Philipp A1 - Drumm, Christian T1 - Lifting XML schemas to ontologies - the concept finder algorithm T2 - MEDIATE 2005 First International Workshop on Mediation in Semantic Web Services Proceedings of the First International Workshop on Mediation in Semantic Web Services (MEDIATE 2005) Y1 - 2005 SP - 113 EP - 122 ER - TY - CHAP A1 - Eggert, Mathias T1 - Understanding the acceptance of smart home-based insurances T2 - Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019 Y1 - 2019 SN - 978-1-7336325-0-8 SP - 1 EP - 15 ER - TY - CHAP A1 - Eggert, Mathias A1 - Stanke, Max-Alexander T1 - Adoption of Integrated Voice Assistants in Health Care– Requirements and Design Guidelines T2 - 15th International Conference on Wirtschaftsinformatik, March 08-11, 2020 Potsdam, Germany Y1 - 2020 U6 - http://dx.doi.org/10.30844/wi_2020_k2-eggert SP - 1 EP - 16 ER - TY - CHAP A1 - Eggert, Mathias A1 - Edelbauer, Thomas Rudolf T1 - Gamified Information Systems for Assisted Living Facilities - Relevant Design Guidelines, Affordances and Adoption Barriers T2 - 15th International Conference on Wirtschaftsinformatik, March 08-11, 2020 Potsdam, Germany Y1 - 2020 U6 - http://dx.doi.org/10.30844/wi_2020_f3-eggert SP - 1 EP - 16 ER - TY - CHAP A1 - Eggert, Mathias A1 - Dyong, Julian T1 - Applying process mining in small and medium sized IT enterprises – challenges and guidelines T2 - International Conference on Business Process Management (BPM 2022) N2 - Process mining gets more and more attention even outside large enterprises and can be a major benefit for small and medium sized enterprises (SMEs) to gain competitive advantages. Applying process mining is challenging, particularly for SMEs because they have less resources and process maturity. So far, IS researchers analyzed process mining challenges with a focus on larger companies. This paper investigates the application of process mining by means of a case study and sheds light into the particular challenges of an IT SME. The results reveal 13 SME process mining challenges and seven guidelines to address them. In this way, the paper contributes to the understanding of process mining application in SME and shows similarities and differences to larger companies. KW - Process mining KW - Challenges KW - Guidelines KW - SME KW - Case Study Y1 - 2022 SN - 978-3-031-16103-2 U6 - http://dx.doi.org/10.1007/978-3-031-16103-2_11 SP - 125 EP - 142 PB - Springer CY - Cham ER - TY - CHAP A1 - Zähl, Philipp M. A1 - Biewendt, Marcel A1 - Wolf, Martin A1 - Eggert, Mathias T1 - Requirements for Competence Developing Games in the Environment of SE Competence Development T2 - Angewandte Forschung in der Wirtschaftsinformatik 2022 N2 - Many of today’s factors make software development more and more complex, such as time pressure, new technologies, IT security risks, et cetera. Thus, a good preparation of current as well as future software developers in terms of a good software engineering education becomes progressively important. As current research shows, Competence Developing Games (CDGs) and Serious Games can offer a potential solution. This paper identifies the necessary requirements for CDGs to be conducive in principle, but especially in software engineering (SE) education. For this purpose, the current state of research was summarized in the context of a literature review. Afterwards, some of the identified requirements as well as some additional requirements were evaluated by a survey in terms of subjective relevance. KW - software engineering KW - requirements KW - competence developing games KW - systematic literature review Y1 - 2022 SN - 978-3-95545-409-8 U6 - http://dx.doi.org/10.30844/AKWI_2022_05 N1 - Tagungsband zur 35. Jahrestagung des Arbeitskreises Wirtschaftsinformatik an Hochschulen für Angewandte Wissenschaften im deutschsprachigen Raum (AKWI) vom 11.09. bis 13.09.2022, ausgerichtet von der Hochschule für Technik und Wirtschaft Berlin (HTW Berlin) und der Hochschule für Wirtschaft und Recht Berlin (HWR Berlin) SP - 73 EP - 88 PB - GITO CY - Berlin ER - TY - CHAP A1 - Schulte, Maximilian A1 - Eggert, Mathias T1 - Predicting hourly bitcoin prices based on long short-term memory neural networks T2 - Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021 N2 - Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movement s and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 %. Y1 - 2021 N1 - 16th International Conference on Wirtschaftsinformatik, March 2021, Essen, Germany ER - TY - CHAP A1 - Eggert, Mathias A1 - Kriska, Melina T1 - Gamification for software development processes – relevant affordances and design principles T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived. Y1 - 2022 SN - 978-0-9981331-5-7 U6 - http://dx.doi.org/10.24251/HICSS.2022.200 N1 - Hawaii International Conference on System Sciences (HICSS) 2022, 04.01.2022 – 07.01.2022 SP - 1614 EP - 1623 PB - HICSS Publishing CY - Honolulu ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER -