@inbook{46205, abstract = {{We present a concept for quantifying evaluative phrases to later compare rating texts numerically instead of just relying on stars or grades. We achievethis by combining deep learning models in an aspect-based sentiment analysis pipeline along with sentiment weighting, polarity, and correlation analyses that combine deep learning results with metadata. The results provide new insights for the medical field. Our application domain, physician reviews, shows that there are millions of review texts on the Internet that cannot yet be comprehensively analyzed because previous studies have focused on explicit aspects from other domains (e.g., products). We identify, extract, and classify implicit and explicit aspect phrases equally from German-language review texts. To do so, we annotated aspect phrases representing reviews on numerous aspects of a physician, medical practice, or practice staff. We apply the best performing transformer model, XLM-RoBERTa, to a large physician review dataset and correlate the results with existing metadata. As a result, we can show different correlations between the sentiment polarity of certain aspect classes (e.g., friendliness, practice equipment) and physicians’ professions (e.g., surgeon, ophthalmologist). As a result, we have individual numerical scores that contain a variety of information based on deep learning algorithms that extract textual (evaluative) information and metadata from the Web.}}, author = {{Kersting, Joschka and Geierhos, Michaela}}, booktitle = {{Data Management Technologies and Applications}}, editor = {{Cuzzocrea, Alfredo and Gusikhin, Oleg and Hammoudi, Slimane and Quix, Christoph}}, isbn = {{9783031378898}}, issn = {{1865-0929}}, pages = {{45--65}}, publisher = {{Springer Nature Switzerland}}, title = {{{Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews}}}, doi = {{10.1007/978-3-031-37890-4_3}}, volume = {{1860}}, year = {{2023}}, } @inproceedings{48595, author = {{Peters, Tobias Martin and Visser, Roel W.}}, booktitle = {{Communications in Computer and Information Science}}, isbn = {{9783031440694}}, issn = {{1865-0929}}, publisher = {{Springer Nature Switzerland}}, title = {{{The Importance of Distrust in AI}}}, doi = {{10.1007/978-3-031-44070-0_15}}, year = {{2023}}, } @inbook{32179, abstract = {{This work addresses the automatic resolution of software requirements. In the vision of On-The-Fly Computing, software services should be composed on demand, based solely on natural language input from human users. To enable this, we build a chatbot solution that works with human-in-the-loop support to receive, analyze, correct, and complete their software requirements. The chatbot is equipped with a natural language processing pipeline and a large knowledge base, as well as sophisticated dialogue management skills to enhance the user experience. Previous solutions have focused on analyzing software requirements to point out errors such as vagueness, ambiguity, or incompleteness. Our work shows how apps can collaborate with users to efficiently produce correct requirements. We developed and compared three different chatbot apps that can work with built-in knowledge. We rely on ChatterBot, DialoGPT and Rasa for this purpose. While DialoGPT provides its own knowledge base, Rasa is the best system to combine the text mining and knowledge solutions at our disposal. The evaluation shows that users accept 73% of the suggested answers from Rasa, while they accept only 63% from DialoGPT or even 36% from ChatterBot.}}, author = {{Kersting, Joschka and Ahmed, Mobeen and Geierhos, Michaela}}, booktitle = {{HCI International 2022 Posters}}, editor = {{Stephanidis, Constantine and Antona, Margherita and Ntoa, Stavroula}}, isbn = {{9783031064166}}, issn = {{1865-0929}}, keywords = {{On-The-Fly Computing, Chatbot, Knowledge Base}}, location = {{Virtual}}, pages = {{419----426}}, publisher = {{Springer International Publishing}}, title = {{{Chatbot-Enhanced Requirements Resolution for Automated Service Compositions}}}, doi = {{10.1007/978-3-031-06417-3_56}}, volume = {{1580}}, year = {{2022}}, } @inbook{33849, abstract = {{Modern traffic control systems are key to cope with current and future traffic challenges. In this paper information obtained from a microscopic traffic estimation using various data sources is used to feed a new developed traffic control approach. The presented method can control a traffic area with multiple traffic light systems (TLS) reacting to individual road users and pedestrians. In contrast to widespread green time extension techniques, this control selects the best phase sequence by analyzing the current traffic state reconstructed in SUMO and its predicted progress. To achieve this, the key aspect of the control strategy is to use Model Predictive Control (MPC). In order to maintain realism for real world applications, among other things, the traffic phase transitions are modelled in detail and integrated within the prediction. For the efficiency, the approach incorporates a fuzzy logic preselection of all phases reducing the computational effort. The evaluation itself is able to be easily adjusted to focus on various objectives like low occupancies, reducing waiting times and emissions, few number of phase transitions etc. determining the best switching times for the selected phases. Exemplary traffic simulations demonstrate the functionality of the MPC-based control and, in addition, some aspects under development like the real-world communication network are also discussed.}}, author = {{Malena, Kevin and Link, Christopher and Bußemas, Leon and Gausemeier, Sandra and Trächtler, Ansgar}}, booktitle = {{Communications in Computer and Information Science}}, editor = {{Klein, Cornel and Jarke, Mathias and Helfert, Markus and Berns, Karsten and Gusikhin, Oleg}}, isbn = {{9783031170973}}, issn = {{1865-0929}}, keywords = {{Traffic control, Traffic estimation, Real-time, MPC, Fuzzy, Isolated intersection, Networked intersection, Sensor fusion}}, pages = {{232–254}}, publisher = {{Springer International Publishing}}, title = {{{Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments}}}, doi = {{10.1007/978-3-031-17098-0_12}}, volume = {{1612}}, year = {{2022}}, } @inproceedings{21483, author = {{Jovanovikj, Ivan and Weidmann, Nils and Yigitbas, Enes and Anjorin, Anthony and Sauer, Stefan and Engels, Gregor}}, booktitle = {{Proceedings of the First International Conference on Systems Modelling and Management, ICSMM 2020 }}, editor = {{Babur, Önder and Denil, Joachim and Vogel-Heuser, Birgit}}, isbn = {{9783030581664}}, issn = {{1865-0929}}, location = {{Bergen, Norway}}, publisher = {{Springer}}, title = {{{A Model-Driven Mutation Framework for Validation of Test Case Migration}}}, doi = {{10.1007/978-3-030-58167-1_2}}, year = {{2020}}, } @inproceedings{22805, author = {{Fockel, Markus and Merschjohann, Sven and Fazal-Baqaie, Masud and Förder, Torsten and Hausmann, Stefan and Waldeck, Boris}}, booktitle = {{European System, Software & Service Process Improvement & Innovation Conference (EuroSPI 2019)}}, issn = {{1865-0929}}, location = {{Edinburgh, UK}}, title = {{{Designing and Integrating IEC 62443 Compliant Threat Analysis}}}, doi = {{10.1007/978-3-030-28005-5_5}}, volume = {{1060}}, year = {{2019}}, } @inbook{4338, abstract = {{Physician review websites are known around the world. Patients review the subjectively experienced quality of medical services supplied to them and publish an overall rating on the Internet, where quantitative grades and qualitative texts come together. On the one hand, these new possibilities reduce the imbalance of power between health care providers and patients, but on the other hand, they can also damage the usually very intimate relationship between health care providers and patients. Review websites must meet these requirements with a high level of responsibility and service quality. In this paper, we look at the situation in Lithuania: Especially, we are interested in the available possibilities of evaluation and interaction, and the quality of a particular review website measured against the available data. We thereby identify quality weaknesses and lay the foundation for future research.}}, author = {{Bäumer, Frederik Simon and Kersting, Joschka and Kuršelis, Vytautas and Geierhos, Michaela}}, booktitle = {{Communications in Computer and Information Science}}, editor = {{Damaševičius, Robertas and Vasiljevienė, Giedrė}}, isbn = {{9783319999715}}, issn = {{1865-0929}}, keywords = {{Lithuanian physician review websites, Medical service ratings}}, location = {{Vilnius, Lithuania}}, pages = {{43--58}}, publisher = {{Springer}}, title = {{{Rate Your Physician: Findings from a Lithuanian Physician Rating Website}}}, doi = {{10.1007/978-3-319-99972-2_4}}, volume = {{920}}, year = {{2018}}, } @inproceedings{4339, abstract = {{On-The-Fly Computing is the vision of covering software needs of end users by fully-automatic compositions of existing software services. End users will receive so-called service compositions tailored to their very individual needs, based on natural language software descriptions. This everyday language may contain inaccuracies and incompleteness, which are well-known challenges in requirements engineering. In addition to existing approaches that try to automatically identify and correct these deficits, there are also new trends to involve users more in the elaboration and refinement process. In this paper, we present the relevant state of the art in the field of automated detection and compensation of multiple inaccuracies in natural language service descriptions and name open challenges needed to be tackled in NL-based software service composition. }}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela}}, booktitle = {{Proceedings of the 24th International Conference on Information and Software Technologies (ICIST 2018)}}, editor = {{Damaševičius, Robertas and Vasiljevienė, Giedrė}}, isbn = {{9783319999715}}, issn = {{1865-0929}}, keywords = {{Inaccuracy detection, Natural language software requirements}}, location = {{Vilnius, Lithuania}}, pages = {{559--570}}, publisher = {{Springer}}, title = {{{NLP in OTF Computing: Current Approaches and Open Challenges}}}, doi = {{10.1007/978-3-319-99972-2_46}}, volume = {{920}}, year = {{2018}}, } @inbook{14856, author = {{Hallmann, Corinna and Burmeister, Sascha Christian and Wissing, Michaela and Suhl, Leena}}, booktitle = {{Communications in Computer and Information Science}}, isbn = {{9783319962702}}, issn = {{1865-0929}}, title = {{{Heuristics and Simulation for Water Tank Optimization}}}, doi = {{10.1007/978-3-319-96271-9_5}}, year = {{2018}}, } @inproceedings{14893, author = {{Ghribi, Ines and Abdallah, Riadh Ben and Khalgui, Mohamed and Platzner, Marco}}, booktitle = {{Communications in Computer and Information Science}}, isbn = {{9783319625683}}, issn = {{1865-0929}}, publisher = {{Springer }}, title = {{{I-Codesign: A Codesign Methodology for Reconfigurable Embedded Systems}}}, doi = {{10.1007/978-3-319-62569-0_8}}, year = {{2017}}, }