--- _id: '53801' abstract: - lang: eng text: 'In this study, we evaluate the impact of gender-biased data from German-language physician reviews on the fairness of fine-tuned language models. For two different downstream tasks, we use data reported to be gender biased and aggregate it with annotations. First, we propose a new approach to aspect-based sentiment analysis that allows identifying, extracting, and classifying implicit and explicit aspect phrases and their polarity within a single model. The second task we present is grade prediction, where we predict the overall grade of a review on the basis of the review text. For both tasks, we train numerous transformer models and evaluate their performance. The aggregation of sensitive attributes, such as a physician’s gender and migration background, with individual text reviews allows us to measure the performance of the models with respect to these sensitive groups. These group-wise performance measures act as extrinsic bias measures for our downstream tasks. In addition, we translate several gender-specific templates of the intrinsic bias metrics into the German language and evaluate our fine-tuned models. Based on this set of tasks, fine-tuned models, and intrinsic and extrinsic bias measures, we perform correlation analyses between intrinsic and extrinsic bias measures. In terms of sensitive groups and effect sizes, our bias measure results show different directions. Furthermore, correlations between measures of intrinsic and extrinsic bias can be observed in different directions. This leads us to conclude that gender-biased data does not inherently lead to biased models. Other variables, such as template dependency for intrinsic measures and label distribution in the data, must be taken into account as they strongly influence the metric results. Therefore, we suggest that metrics and templates should be chosen according to the given task and the biases to be assessed. ' article_number: '102235' article_type: original author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Falk full_name: Maoro, Falk last_name: Maoro - first_name: Michaela full_name: Geierhos, Michaela last_name: Geierhos citation: ama: 'Kersting J, Maoro F, Geierhos M. Towards comparable ratings: Exploring bias in German physician reviews. Data & Knowledge Engineering. 2023;148. doi:10.1016/j.datak.2023.102235' apa: 'Kersting, J., Maoro, F., & Geierhos, M. (2023). Towards comparable ratings: Exploring bias in German physician reviews. Data & Knowledge Engineering, 148, Article 102235. https://doi.org/10.1016/j.datak.2023.102235' bibtex: '@article{Kersting_Maoro_Geierhos_2023, title={Towards comparable ratings: Exploring bias in German physician reviews}, volume={148}, DOI={10.1016/j.datak.2023.102235}, number={102235}, journal={Data & Knowledge Engineering}, publisher={Elsevier}, author={Kersting, Joschka and Maoro, Falk and Geierhos, Michaela}, year={2023} }' chicago: 'Kersting, Joschka, Falk Maoro, and Michaela Geierhos. “Towards Comparable Ratings: Exploring Bias in German Physician Reviews.” Data & Knowledge Engineering 148 (2023). https://doi.org/10.1016/j.datak.2023.102235.' ieee: 'J. Kersting, F. Maoro, and M. Geierhos, “Towards comparable ratings: Exploring bias in German physician reviews,” Data & Knowledge Engineering, vol. 148, Art. no. 102235, 2023, doi: 10.1016/j.datak.2023.102235.' mla: 'Kersting, Joschka, et al. “Towards Comparable Ratings: Exploring Bias in German Physician Reviews.” Data & Knowledge Engineering, vol. 148, 102235, Elsevier, 2023, doi:10.1016/j.datak.2023.102235.' short: J. Kersting, F. Maoro, M. Geierhos, Data & Knowledge Engineering 148 (2023). date_created: 2024-04-30T12:30:56Z date_updated: 2024-04-30T12:41:14Z ddc: - '004' department: - _id: '579' doi: 10.1016/j.datak.2023.102235 file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2024-04-30T12:34:35Z date_updated: 2024-04-30T12:34:35Z file_id: '53802' file_name: Kersting 2023.pdf file_size: 1381398 relation: main_file success: 1 file_date_updated: 2024-04-30T12:34:35Z funded_apc: '1' has_accepted_license: '1' intvolume: ' 148' keyword: - Language model fairness - Aspect phrase classification - Grade prediction - Physician reviews language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.1016/j.datak.2023.102235 ' oa: '1' project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' publication: Data & Knowledge Engineering publication_identifier: issn: - 0169-023X publication_status: published publisher: Elsevier status: public title: 'Towards comparable ratings: Exploring bias in German physician reviews' type: journal_article user_id: '58701' volume: 148 year: '2023' ... --- _id: '44323' abstract: - lang: eng text: "Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods.\r\nImplicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit\r\n(3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified?\r\nThe uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights.\r\nAs a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain." author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting citation: ama: Kersting J. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München ; 2023. apa: Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München . bibtex: '@book{Kersting_2023, place={Neubiberg}, title={Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}, publisher={Universität der Bundeswehr München }, author={Kersting, Joschka}, year={2023} }' chicago: 'Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' ieee: 'J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' mla: Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München , 2023. short: J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023. date_created: 2023-05-02T12:54:00Z date_updated: 2023-07-03T12:29:50Z department: - _id: '579' - _id: '7' language: - iso: ger page: '208' place: Neubiberg project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Subproject B1' publication_status: published publisher: 'Universität der Bundeswehr München ' related_material: link: - relation: supplementary_material url: https://athene-forschung.unibw.de/145003 status: public supervisor: - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 title: Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining type: dissertation user_id: '58701' year: '2023' ... --- _id: '46205' abstract: - lang: eng text: 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: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews. In: Cuzzocrea A, Gusikhin O, Hammoudi S, Quix C, eds. Data Management Technologies and Applications. Vol 1860. Communications in Computer and Information Science. Springer Nature Switzerland; 2023:45-65. doi:10.1007/978-3-031-37890-4_3' apa: 'Kersting, J., & Geierhos, M. (2023). Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews. In A. Cuzzocrea, O. Gusikhin, S. Hammoudi, & C. Quix (Eds.), Data Management Technologies and Applications (Vol. 1860, pp. 45–65). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-37890-4_3' bibtex: '@inbook{Kersting_Geierhos_2023, place={Cham}, series={Communications in Computer and Information Science}, title={Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews}, volume={1860}, DOI={10.1007/978-3-031-37890-4_3}, booktitle={Data Management Technologies and Applications}, publisher={Springer Nature Switzerland}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Cuzzocrea, Alfredo and Gusikhin, Oleg and Hammoudi, Slimane and Quix, Christoph}, year={2023}, pages={45–65}, collection={Communications in Computer and Information Science} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews.” In Data Management Technologies and Applications, edited by Alfredo Cuzzocrea, Oleg Gusikhin, Slimane Hammoudi, and Christoph Quix, 1860:45–65. Communications in Computer and Information Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-37890-4_3.' ieee: 'J. Kersting and M. Geierhos, “Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews,” in Data Management Technologies and Applications, vol. 1860, A. Cuzzocrea, O. Gusikhin, S. Hammoudi, and C. Quix, Eds. Cham: Springer Nature Switzerland, 2023, pp. 45–65.' mla: 'Kersting, Joschka, and Michaela Geierhos. “Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews.” Data Management Technologies and Applications, edited by Alfredo Cuzzocrea et al., vol. 1860, Springer Nature Switzerland, 2023, pp. 45–65, doi:10.1007/978-3-031-37890-4_3.' short: 'J. Kersting, M. Geierhos, in: A. Cuzzocrea, O. Gusikhin, S. Hammoudi, C. Quix (Eds.), Data Management Technologies and Applications, Springer Nature Switzerland, Cham, 2023, pp. 45–65.' date_created: 2023-07-28T15:03:14Z date_updated: 2023-07-28T15:11:10Z ddc: - '004' department: - _id: '579' doi: 10.1007/978-3-031-37890-4_3 editor: - first_name: Alfredo full_name: Cuzzocrea, Alfredo last_name: Cuzzocrea - first_name: Oleg full_name: Gusikhin, Oleg last_name: Gusikhin - first_name: Slimane full_name: Hammoudi, Slimane last_name: Hammoudi - first_name: Christoph full_name: Quix, Christoph last_name: Quix file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2023-07-28T15:10:48Z date_updated: 2023-07-28T15:10:48Z file_id: '46207' file_name: Kersting and Geierhos (2023), Kersting2023b.pdf file_size: 746336 relation: main_file success: 1 file_date_updated: 2023-07-28T15:10:48Z has_accepted_license: '1' intvolume: ' 1860' language: - iso: eng page: 45-65 place: Cham project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' publication: Data Management Technologies and Applications publication_identifier: isbn: - '9783031378898' - '9783031378904' issn: - 1865-0929 - 1865-0937 publication_status: published publisher: Springer Nature Switzerland series_title: Communications in Computer and Information Science status: public title: 'Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews' type: book_chapter user_id: '58701' volume: 1860 year: '2023' ... --- _id: '32179' abstract: - lang: eng text: 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: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Mobeen full_name: Ahmed, Mobeen last_name: Ahmed - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Ahmed M, Geierhos M. Chatbot-Enhanced Requirements Resolution for Automated Service Compositions. In: Stephanidis C, Antona M, Ntoa S, eds. HCI International 2022 Posters. Vol 1580. Communications in Computer and Information Science (CCIS). Springer International Publishing; 2022:419--426. doi:10.1007/978-3-031-06417-3_56' apa: Kersting, J., Ahmed, M., & Geierhos, M. (2022). Chatbot-Enhanced Requirements Resolution for Automated Service Compositions. In C. Stephanidis, M. Antona, & S. Ntoa (Eds.), HCI International 2022 Posters (Vol. 1580, pp. 419--426). Springer International Publishing. https://doi.org/10.1007/978-3-031-06417-3_56 bibtex: '@inbook{Kersting_Ahmed_Geierhos_2022, place={Cham, Switzerland}, series={Communications in Computer and Information Science (CCIS)}, title={Chatbot-Enhanced Requirements Resolution for Automated Service Compositions}, volume={1580}, DOI={10.1007/978-3-031-06417-3_56}, booktitle={HCI International 2022 Posters}, publisher={Springer International Publishing}, author={Kersting, Joschka and Ahmed, Mobeen and Geierhos, Michaela}, editor={Stephanidis, Constantine and Antona, Margherita and Ntoa, Stavroula}, year={2022}, pages={419--426}, collection={Communications in Computer and Information Science (CCIS)} }' chicago: 'Kersting, Joschka, Mobeen Ahmed, and Michaela Geierhos. “Chatbot-Enhanced Requirements Resolution for Automated Service Compositions.” In HCI International 2022 Posters, edited by Constantine Stephanidis, Margherita Antona, and Stavroula Ntoa, 1580:419--426. Communications in Computer and Information Science (CCIS). Cham, Switzerland: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-06417-3_56.' ieee: 'J. Kersting, M. Ahmed, and M. Geierhos, “Chatbot-Enhanced Requirements Resolution for Automated Service Compositions,” in HCI International 2022 Posters, vol. 1580, C. Stephanidis, M. Antona, and S. Ntoa, Eds. Cham, Switzerland: Springer International Publishing, 2022, pp. 419--426.' mla: Kersting, Joschka, et al. “Chatbot-Enhanced Requirements Resolution for Automated Service Compositions.” HCI International 2022 Posters, edited by Constantine Stephanidis et al., vol. 1580, Springer International Publishing, 2022, pp. 419--426, doi:10.1007/978-3-031-06417-3_56. short: 'J. Kersting, M. Ahmed, M. Geierhos, in: C. Stephanidis, M. Antona, S. Ntoa (Eds.), HCI International 2022 Posters, Springer International Publishing, Cham, Switzerland, 2022, pp. 419--426.' conference: end_date: 2022-07-01 location: Virtual name: 24th International Conference on Human-Computer Interaction (HCII 2022) start_date: 2022-06-26 date_created: 2022-06-27T09:27:06Z date_updated: 2022-11-28T13:22:16Z ddc: - '004' department: - _id: '579' doi: 10.1007/978-3-031-06417-3_56 editor: - first_name: Constantine full_name: Stephanidis, Constantine last_name: Stephanidis - first_name: Margherita full_name: Antona, Margherita last_name: Antona - first_name: Stavroula full_name: Ntoa, Stavroula last_name: Ntoa file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2022-11-28T13:21:32Z date_updated: 2022-11-28T13:21:32Z file_id: '34150' file_name: Kersting et al. (2022), Kersting2022.pdf file_size: 1153017 relation: main_file success: 1 file_date_updated: 2022-11-28T13:21:32Z has_accepted_license: '1' intvolume: ' 1580' keyword: - On-The-Fly Computing - Chatbot - Knowledge Base language: - iso: eng page: 419--426 place: Cham, Switzerland project: - _id: '1' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' name: 'SFB 901 - B1: SFB 901 - Subproject B1' publication: HCI International 2022 Posters publication_identifier: isbn: - '9783031064166' - '9783031064173' issn: - 1865-0929 - 1865-0937 publication_status: published publisher: Springer International Publishing related_material: link: - relation: confirmation url: https://link.springer.com/chapter/10.1007/978-3-031-06417-3_56 series_title: Communications in Computer and Information Science (CCIS) status: public title: Chatbot-Enhanced Requirements Resolution for Automated Service Compositions type: book_chapter user_id: '58701' volume: 1580 year: '2022' ... --- _id: '53803' citation: ama: Kersting J, ed. PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications. IARIA; 2022. apa: Kersting, J. (Ed.). (2022). PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications. IARIA. bibtex: '@book{Kersting_2022, place={Barcelona, Spain}, title={PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications}, publisher={IARIA}, year={2022} }' chicago: 'Kersting, Joschka, ed. PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications. Barcelona, Spain: IARIA, 2022.' ieee: 'J. Kersting, Ed., PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications. Barcelona, Spain: IARIA, 2022.' mla: Kersting, Joschka, editor. PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications. IARIA, 2022. short: J. Kersting, ed., PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications, IARIA, Barcelona, Spain, 2022. conference: end_date: 2022-04-28 location: Barcelona, Spain name: The Fourteenth International Conferences on Pervasive Patterns and Applications -- PATTERNS 2022 start_date: 2022-04-24 date_created: 2024-04-30T14:02:14Z date_updated: 2024-04-30T14:05:40Z ddc: - '004' department: - _id: '579' editor: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2024-04-30T14:01:07Z date_updated: 2024-04-30T14:01:07Z file_id: '53804' file_name: patterns_2022_full.pdf file_size: 4578901 relation: main_file success: 1 file_date_updated: 2024-04-30T14:01:07Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://www.thinkmind.org/index.php?view=instance&instance=PATTERNS+2022 oa: '1' place: Barcelona, Spain project: - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' publication_identifier: unknown: - 978-1-61208-953-9 publication_status: published publisher: IARIA status: public title: PATTERNS 2022 The Fourteenth International Conferences on Pervasive Patterns and Applications type: conference_editor user_id: '58701' year: '2022' ... --- _id: '17905' abstract: - lang: eng text: 'This chapter concentrates on aspect-based sentiment analysis, a form of opinion mining where algorithms detect sentiments expressed about features of products, services, etc. We especially focus on novel approaches for aspect phrase extraction and classification trained on feature-rich datasets. Here, we present two new datasets, which we gathered from the linguistically rich domain of physician reviews, as other investigations have mainly concentrated on commercial reviews and social media reviews so far. To give readers a better understanding of the underlying datasets, we describe the annotation process and inter-annotator agreement in detail. In our research, we automatically assess implicit mentions or indications of specific aspects. To do this, we propose and utilize neural network models that perform the here-defined aspect phrase extraction and classification task, achieving F1-score values of about 80% and accuracy values of more than 90%. As we apply our models to a comparatively complex domain, we obtain promising results. ' author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks. In: Loukanova R, ed. Natural Language Processing in Artificial Intelligence -- NLPinAI 2020. Vol 939. Studies in Computational Intelligence (SCI). Cham: Springer; 2021:163--189. doi:10.1007/978-3-030-63787-3_6' apa: 'Kersting, J., & Geierhos, M. (2021). Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks. In R. Loukanova (Ed.), Natural Language Processing in Artificial Intelligence -- NLPinAI 2020 (Vol. 939, pp. 163--189). Cham: Springer. https://doi.org/10.1007/978-3-030-63787-3_6' bibtex: '@inbook{Kersting_Geierhos_2021, place={Cham}, series={Studies in Computational Intelligence (SCI)}, title={Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks}, volume={939}, DOI={10.1007/978-3-030-63787-3_6}, booktitle={Natural Language Processing in Artificial Intelligence -- NLPinAI 2020}, publisher={Springer}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Loukanova, RoussankaEditor}, year={2021}, pages={163--189}, collection={Studies in Computational Intelligence (SCI)} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks.” In Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, edited by Roussanka Loukanova, 939:163--189. Studies in Computational Intelligence (SCI). Cham: Springer, 2021. https://doi.org/10.1007/978-3-030-63787-3_6.' ieee: 'J. Kersting and M. Geierhos, “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks,” in Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, vol. 939, R. Loukanova, Ed. Cham: Springer, 2021, pp. 163--189.' mla: Kersting, Joschka, and Michaela Geierhos. “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks.” Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, edited by Roussanka Loukanova, vol. 939, Springer, 2021, pp. 163--189, doi:10.1007/978-3-030-63787-3_6. short: 'J. Kersting, M. Geierhos, in: R. Loukanova (Ed.), Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, Springer, Cham, 2021, pp. 163--189.' date_created: 2020-08-13T09:29:52Z date_updated: 2022-01-06T06:53:23Z ddc: - '000' department: - _id: '579' doi: 10.1007/978-3-030-63787-3_6 editor: - first_name: Roussanka full_name: Loukanova, Roussanka last_name: Loukanova file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2021-04-08T08:14:05Z date_updated: 2021-04-08T08:14:05Z file_id: '21594' file_name: Kersting-Geierhos2021_Chapter_TowardsAspectExtractionAndClas.pdf file_size: 512065 relation: main_file success: 1 file_date_updated: 2021-04-08T08:14:05Z has_accepted_license: '1' intvolume: ' 939' language: - iso: eng page: '163--189 ' place: Cham project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Natural Language Processing in Artificial Intelligence -- NLPinAI 2020 publication_identifier: unknown: - 978-3-030-63786-6 ; 978-3-030-63787-3 publication_status: published publisher: Springer series_title: Studies in Computational Intelligence (SCI) status: public title: Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks type: book_chapter user_id: '58701' volume: 939 year: '2021' ... --- _id: '22051' author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Well-being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations. In: Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021). SCITEPRESS; 2021:275--284.' apa: 'Kersting, J., & Geierhos, M. (2021). Well-being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations. Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), 275--284.' bibtex: '@inproceedings{Kersting_Geierhos_2021, place={Online}, title={Well-being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations}, booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021)}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos, Michaela}, year={2021}, pages={275--284} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Well-Being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations.” In Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), 275--284. Online: SCITEPRESS, 2021.' ieee: 'J. Kersting and M. Geierhos, “Well-being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations,” in Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), Online, 2021, pp. 275--284.' mla: 'Kersting, Joschka, and Michaela Geierhos. “Well-Being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations.” Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), SCITEPRESS, 2021, pp. 275--284.' short: 'J. Kersting, M. Geierhos, in: Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), SCITEPRESS, Online, 2021, pp. 275--284.' conference: end_date: 2021-07-08 location: Online name: 10th International Conference on Data Science, Technology and Applications (DATA 2021) start_date: 2021-07-06 date_created: 2021-05-07T16:27:27Z date_updated: 2022-01-06T06:55:23Z department: - _id: '579' language: - iso: eng page: 275--284 place: Online project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021) publication_status: published publisher: SCITEPRESS status: public title: 'Well-being in Plastic Surgery: Deep Learning Reveals Patients'' Evaluations' type: conference user_id: '58701' year: '2021' ... --- _id: '22052' abstract: - lang: eng text: In this study, we describe a text processing pipeline that transforms user-generated text into structured data. To do this, we train neural and transformer-based models for aspect-based sentiment analysis. As most research deals with explicit aspects from product or service data, we extract and classify implicit and explicit aspect phrases from German-language physician review texts. Patients often rate on the basis of perceived friendliness or competence. The vocabulary is difficult, the topic sensitive, and the data user-generated. The aspect phrases come with various wordings using insertions and are not noun-based, which makes the presented case equally relevant and reality-based. To find complex, indirect aspect phrases, up-to-date deep learning approaches must be combined with supervised training data. We describe three aspect phrase datasets, one of them new, as well as a newly annotated aspect polarity dataset. Alongside this, we build an algorithm to rate the aspect phrase importance. All in all, we train eight transformers on the new raw data domain, compare 54 neural aspect extraction models and, based on this, create eight aspect polarity models for our pipeline. These models are evaluated by using Precision, Recall, and F-Score measures. Finally, we evaluate our aspect phrase importance measure algorithm. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting. In: Kapetanios E, Horacek H, Métais E, Meziane F, eds. Natural Language Processing and Information Systems. Vol 12801. Lecture Notes in Computer Science. Springer; 2021:231--242.' apa: Kersting, J., & Geierhos, M. (2021). Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting. In E. Kapetanios, H. Horacek, E. Métais, & F. Meziane (Eds.), Natural Language Processing and Information Systems (Vol. 12801, pp. 231--242). Springer. bibtex: '@inbook{Kersting_Geierhos_2021, place={Saarbrücken, Germany}, series={Lecture Notes in Computer Science}, title={Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting}, volume={12801}, booktitle={Natural Language Processing and Information Systems}, publisher={Springer}, author={Kersting, Joschka and Geierhos, Michaela}, editor={Kapetanios, Epaminondas and Horacek, Helmut and Métais, Elisabeth and Meziane, Farid}, year={2021}, pages={231--242}, collection={Lecture Notes in Computer Science} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting.” In Natural Language Processing and Information Systems, edited by Epaminondas Kapetanios, Helmut Horacek, Elisabeth Métais, and Farid Meziane, 12801:231--242. Lecture Notes in Computer Science. Saarbrücken, Germany: Springer, 2021.' ieee: 'J. Kersting and M. Geierhos, “Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting,” in Natural Language Processing and Information Systems, vol. 12801, E. Kapetanios, H. Horacek, E. Métais, and F. Meziane, Eds. Saarbrücken, Germany: Springer, 2021, pp. 231--242.' mla: Kersting, Joschka, and Michaela Geierhos. “Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting.” Natural Language Processing and Information Systems, edited by Epaminondas Kapetanios et al., vol. 12801, Springer, 2021, pp. 231--242. short: 'J. Kersting, M. Geierhos, in: E. Kapetanios, H. Horacek, E. Métais, F. Meziane (Eds.), Natural Language Processing and Information Systems, Springer, Saarbrücken, Germany, 2021, pp. 231--242.' conference: end_date: 2021-06-25 location: Saarbrücken, Germany name: 26th International Conference on Natural Language & Information Systems (NLDB 2021) start_date: 2021-06-23 date_created: 2021-05-07T16:31:05Z date_updated: 2022-07-14T08:00:56Z ddc: - '004' department: - _id: '579' editor: - first_name: Epaminondas full_name: Kapetanios, Epaminondas last_name: Kapetanios - first_name: Helmut full_name: Horacek, Helmut last_name: Horacek - first_name: Elisabeth full_name: Métais, Elisabeth last_name: Métais - first_name: Farid full_name: Meziane, Farid last_name: Meziane file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2022-07-14T08:00:35Z date_updated: 2022-07-14T08:00:35Z file_id: '32362' file_name: Kersting & Geierhos (2021b), Kersting2021b.pdf file_size: 506329 relation: main_file success: 1 file_date_updated: 2022-07-14T08:00:35Z has_accepted_license: '1' intvolume: ' 12801' language: - iso: eng page: 231--242 place: Saarbrücken, Germany project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Natural Language Processing and Information Systems publication_status: published publisher: Springer series_title: Lecture Notes in Computer Science status: public title: Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting type: book_chapter user_id: '58701' volume: 12801 year: '2021' ... --- _id: '17347' abstract: - lang: eng text: Peer-to-Peer news portals allow Internet users to write news articles and make them available online to interested readers. Despite the fact that authors are free in their choice of topics, there are a number of quality characteristics that an article must meet before it is published. In addition to meaningful titles, comprehensibly written texts and meaning- ful images, relevant tags are an important criteria for the quality of such news. In this case study, we discuss the challenges and common mistakes that Peer-to-Peer reporters face when tagging news and how incorrect information can be corrected through the orchestration of existing Natu- ral Language Processing services. Lastly, we use this illustrative example to give insight into the challenges of dealing with bottom-up taxonomies. author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Bianca full_name: Buff, Bianca last_name: Buff - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Kersting J, Buff B, Geierhos M. Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging. In: Audrius L, Rita B, Daina G, Vilma S, eds. Information and Software Technologies. Vol 1283. Communications in Computer and Information Science. Springer; 2020:368--382. doi:https://doi.org/10.1007/978-3-030-59506-7_30' apa: 'Bäumer, F. S., Kersting, J., Buff, B., & Geierhos, M. (2020). Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging. In L. Audrius, B. Rita, G. Daina, & S. Vilma (Eds.), Information and Software Technologies (Vol. 1283, pp. 368--382). Kaunas, Litauen: Springer. https://doi.org/10.1007/978-3-030-59506-7_30' bibtex: '@inbook{Bäumer_Kersting_Buff_Geierhos_2020, series={Communications in Computer and Information Science}, title={Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging}, volume={1283}, DOI={https://doi.org/10.1007/978-3-030-59506-7_30}, booktitle={Information and Software Technologies}, publisher={Springer}, author={Bäumer, Frederik Simon and Kersting, Joschka and Buff, Bianca and Geierhos, Michaela}, editor={Audrius, Lopata and Rita, Butkienė and Daina, Gudonienė and Vilma, SukackėEditors}, year={2020}, pages={368--382}, collection={Communications in Computer and Information Science} }' chicago: 'Bäumer, Frederik Simon, Joschka Kersting, Bianca Buff, and Michaela Geierhos. “Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging.” In Information and Software Technologies, edited by Lopata Audrius, Butkienė Rita, Gudonienė Daina, and Sukackė Vilma, 1283:368--382. Communications in Computer and Information Science. Springer, 2020. https://doi.org/10.1007/978-3-030-59506-7_30.' ieee: 'F. S. Bäumer, J. Kersting, B. Buff, and M. Geierhos, “Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging,” in Information and Software Technologies, vol. 1283, L. Audrius, B. Rita, G. Daina, and S. Vilma, Eds. Springer, 2020, pp. 368--382.' mla: 'Bäumer, Frederik Simon, et al. “Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging.” Information and Software Technologies, edited by Lopata Audrius et al., vol. 1283, Springer, 2020, pp. 368--382, doi:https://doi.org/10.1007/978-3-030-59506-7_30.' short: 'F.S. Bäumer, J. Kersting, B. Buff, M. Geierhos, in: L. Audrius, B. Rita, G. Daina, S. Vilma (Eds.), Information and Software Technologies, Springer, 2020, pp. 368--382.' conference: end_date: 2020-10-17 location: Kaunas, Litauen name: 26th International Conference on Information and Software Technologies (ICIST 2020) start_date: 2020-10-15 date_created: 2020-06-26T14:23:52Z date_updated: 2022-01-06T06:53:08Z ddc: - '004' department: - _id: '579' - _id: '1' - _id: '36' doi: https://doi.org/10.1007/978-3-030-59506-7_30 editor: - first_name: Lopata full_name: Audrius, Lopata last_name: Audrius - first_name: Butkienė full_name: Rita, Butkienė last_name: Rita - first_name: Gudonienė full_name: Daina, Gudonienė last_name: Daina - first_name: Sukackė full_name: Vilma, Sukackė last_name: Vilma file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-11-07T19:47:30Z date_updated: 2020-11-07T19:47:30Z file_id: '20309' file_name: Bäumer et al. (2020), Baeumer2020.pdf .pdf file_size: 599881 relation: main_file success: 1 file_date_updated: 2020-11-07T19:47:30Z has_accepted_license: '1' intvolume: ' 1283' language: - iso: eng page: 368--382 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Information and Software Technologies publication_status: published publisher: Springer series_title: Communications in Computer and Information Science status: public title: 'Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging' type: book_chapter user_id: '58701' volume: 1283 year: '2020' ... --- _id: '18686' author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer citation: ama: 'Kersting J, Bäumer FS. SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020. IADIS; 2020:119--123.' apa: 'Kersting, J., & Bäumer, F. S. (2020). SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123.' bibtex: '@inproceedings{Kersting_Bäumer_2020, title={SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH}, booktitle={PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020}, publisher={IADIS}, author={Kersting, Joschka and Bäumer, Frederik Simon}, year={2020}, pages={119--123} }' chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123. IADIS, 2020.' ieee: 'J. Kersting and F. S. Bäumer, “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, Lisbon, Portugal, 2020, pp. 119--123.' mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.' short: 'J. Kersting, F.S. Bäumer, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.' conference: end_date: 20.11.2020 location: Lisbon, Portugal name: 17th International Conference on Applied Computing start_date: 18.11.2020 date_created: 2020-08-31T10:59:54Z date_updated: 2022-01-06T06:53:51Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-11-19T17:29:03Z date_updated: 2020-11-19T17:29:03Z file_id: '20443' file_name: Kersting & Bäumer (2020), Kersting2020d.pdf file_size: 1064877 relation: main_file success: 1 file_date_updated: 2020-11-19T17:29:03Z has_accepted_license: '1' keyword: - Software Requirements - Natural Language Processing - Transfer Learning - On-The-Fly Computing language: - iso: eng page: 119--123 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020 publisher: IADIS status: public title: 'SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH' type: conference user_id: '58701' year: '2020' ... --- _id: '15580' abstract: - lang: eng text: This paper deals with aspect phrase extraction and classification in sentiment analysis. We summarize current approaches and datasets from the domain of aspect-based sentiment analysis. This domain detects sentiments expressed for individual aspects in unstructured text data. So far, mainly commercial user reviews for products or services such as restaurants were investigated. We here present our dataset consisting of German physician reviews, a sensitive and linguistically complex field. Furthermore, we describe the annotation process of a dataset for supervised learning with neural networks. Moreover, we introduce our model for extracting and classifying aspect phrases in one step, which obtains an F1-score of 80%. By applying it to a more complex domain, our approach and results outperform previous approaches. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020). Setúbal, Portugal: SCITEPRESS; 2020:391--400.' apa: 'Kersting, J., & Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400). Setúbal, Portugal: SCITEPRESS.' bibtex: '@inproceedings{Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={Aspect Phrase Extraction in Sentiment Analysis with Deep Learning}, booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020)}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos, Michaela}, year={2020}, pages={391--400} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning.” In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), 391--400. Setúbal, Portugal: SCITEPRESS, 2020.' ieee: J. Kersting and M. Geierhos, “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning,” in Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), Valetta, Malta, 2020, pp. 391--400. mla: Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning.” Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, 2020, pp. 391--400. short: 'J. Kersting, M. Geierhos, in: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, Setúbal, Portugal, 2020, pp. 391--400.' conference: location: Valetta, Malta name: International Conference on Agents and Artificial Intelligence (ICAART) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI) date_created: 2020-01-15T08:35:07Z date_updated: 2022-01-06T06:52:29Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:27:00Z date_updated: 2020-09-18T09:27:00Z file_id: '19576' file_name: Kersting & Geierhos (2020), Kersting2020.pdf file_size: 421780 relation: main_file success: 1 file_date_updated: 2020-09-18T09:27:00Z has_accepted_license: '1' keyword: - Deep Learning - Natural Language Processing - Aspect-based Sentiment Analysis language: - iso: eng page: 391--400 place: Setúbal, Portugal project: - _id: '3' name: SFB 901 - Project Area B - _id: '1' name: SFB 901 - _id: '9' name: SFB 901 - Subproject B1 publication: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) publisher: SCITEPRESS status: public title: Aspect Phrase Extraction in Sentiment Analysis with Deep Learning type: conference user_id: '58701' year: '2020' ... --- _id: '15582' abstract: - lang: eng text: When it comes to increased digitization in the health care domain, privacy is a relevant topic nowadays. This relates to patient data, electronic health records or physician reviews published online, for instance. There exist different approaches to the protection of individuals’ privacy, which focus on the anonymization and masking of personal information subsequent to their mining. In the medical domain in particular, measures to protect the privacy of patients are of high importance due to the amount of sensitive data that is involved (e.g. age, gender, illnesses, medication). While privacy breaches in structured data can be detected more easily, disclosure in written texts is more difficult to find automatically due to the unstructured nature of natural language. Therefore, we take a detailed look at existing research on areas related to privacy protection. Likewise, we review approaches to the automatic detection of privacy disclosure in different types of medical data. We provide a survey of several studies concerned with privacy breaches in the medical domain with a focus on Physician Review Websites (PRWs). Finally, we briefly develop implications and directions for further research. author: - first_name: Bianca full_name: Buff, Bianca last_name: Buff - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Buff B, Kersting J, Geierhos M. Detection of Privacy Disclosure in the Medical Domain: A Survey. In: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020). Setúbal, Portugal: SCITEPRESS; 2020:630--637.' apa: 'Buff, B., Kersting, J., & Geierhos, M. (2020). Detection of Privacy Disclosure in the Medical Domain: A Survey. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020) (pp. 630--637). Setúbal, Portugal: SCITEPRESS.' bibtex: '@inproceedings{Buff_Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={Detection of Privacy Disclosure in the Medical Domain: A Survey}, booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020)}, publisher={SCITEPRESS}, author={Buff, Bianca and Kersting, Joschka and Geierhos, Michaela}, year={2020}, pages={630--637} }' chicago: 'Buff, Bianca, Joschka Kersting, and Michaela Geierhos. “Detection of Privacy Disclosure in the Medical Domain: A Survey.” In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), 630--637. Setúbal, Portugal: SCITEPRESS, 2020.' ieee: 'B. Buff, J. Kersting, and M. Geierhos, “Detection of Privacy Disclosure in the Medical Domain: A Survey,” in Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), Valetta, Malta, 2020, pp. 630--637.' mla: 'Buff, Bianca, et al. “Detection of Privacy Disclosure in the Medical Domain: A Survey.” Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), SCITEPRESS, 2020, pp. 630--637.' short: 'B. Buff, J. Kersting, M. Geierhos, in: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), SCITEPRESS, Setúbal, Portugal, 2020, pp. 630--637.' conference: location: Valetta, Malta name: International Conference on Pattern Recognition Applications and Methods (ICPRAM) date_created: 2020-01-15T08:49:25Z date_updated: 2022-01-06T06:52:30Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:25:30Z date_updated: 2020-09-18T09:25:30Z file_id: '19574' file_name: Buff et al. (2020), Buff2020.pdf file_size: 287956 relation: main_file success: 1 file_date_updated: 2020-09-18T09:25:30Z has_accepted_license: '1' keyword: - Identity Disclosure - Privacy Protection - Physician Review Website - De-Anonymization - Medical Domain language: - iso: eng page: 630--637 place: Setúbal, Portugal project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020) publisher: SCITEPRESS status: public title: 'Detection of Privacy Disclosure in the Medical Domain: A Survey' type: conference user_id: '58701' year: '2020' ... --- _id: '15635' author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis. In: Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference. North Miami Beach, FL, USA: AAAI; 2020:282--285.' apa: 'Kersting, J., & Geierhos, M. (2020). Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis. In Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference (pp. 282--285). North Miami Beach, FL, USA: AAAI.' bibtex: '@inproceedings{Kersting_Geierhos_2020, place={North Miami Beach, FL, USA}, title={Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis}, booktitle={Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference}, publisher={AAAI}, author={Kersting, Joschka and Geierhos, Michaela}, year={2020}, pages={282--285} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis.” In Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference, 282--285. North Miami Beach, FL, USA: AAAI, 2020.' ieee: J. Kersting and M. Geierhos, “Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis,” in Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference, North Miami Beach, FL, USA, 2020, pp. 282--285. mla: Kersting, Joschka, and Michaela Geierhos. “Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis.” Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference, AAAI, 2020, pp. 282--285. short: 'J. Kersting, M. Geierhos, in: Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference, AAAI, North Miami Beach, FL, USA, 2020, pp. 282--285.' conference: end_date: 2020-05-20 location: North Miami Beach, FL, USA name: The 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference start_date: 2020-05-17 date_created: 2020-01-24T09:10:09Z date_updated: 2022-01-06T06:52:31Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:39:08Z date_updated: 2020-09-18T09:39:08Z file_id: '19582' file_name: Kersting & Geierhos (2020b), Kersting2020b.pdf file_size: 464976 relation: main_file success: 1 file_date_updated: 2020-09-18T09:39:08Z has_accepted_license: '1' language: - iso: eng page: 282--285 place: North Miami Beach, FL, USA project: - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 - _id: '1' name: SFB 901 publication: Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference publisher: AAAI status: public title: Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis type: conference user_id: '58701' year: '2020' ... --- _id: '15256' abstract: - lang: eng text: This paper deals with online customer reviews of local multi-service providers. While many studies investigate product reviews and online labour markets with service providers delivering intangible products “over the wire”, we focus on websites where providers offer multiple distinct services that can be booked, paid and reviewed online but are performed locally offline. This type of service providers has so far been neglected in the literature. This paper analyses reviews and applies sentiment analysis. It aims to gain new insights into local multi-service providers’ performance. There is a broad literature range presented with regard to the topics addressed. The results show, among other things, that providers with good ratings continue to perform well over time. We find that many positive reviews seem to encourage sales. On average, quantitative star ratings and qualitative ratings in the form of review texts match. Further results are also achieved in this study. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers. In: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods. Setúbal, Portugal: SCITEPRESS; 2020:263--272.' apa: 'Kersting, J., & Geierhos, M. (2020). What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (pp. 263--272). Setúbal, Portugal: SCITEPRESS.' bibtex: '@inproceedings{Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers}, booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos, Michaela}, year={2020}, pages={263--272} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers.” In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 263--272. Setúbal, Portugal: SCITEPRESS, 2020.' ieee: J. Kersting and M. Geierhos, “What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers,” in Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, Valetta, Malta, 2020, pp. 263--272. mla: Kersting, Joschka, and Michaela Geierhos. “What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers.” Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, SCITEPRESS, 2020, pp. 263--272. short: 'J. Kersting, M. Geierhos, in: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, SCITEPRESS, Setúbal, Portugal, 2020, pp. 263--272.' conference: location: Valetta, Malta name: International Conference on Pattern Recognition Applications and Methods (ICPRAM) date_created: 2019-12-06T13:09:42Z date_updated: 2022-01-06T06:52:19Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:27:41Z date_updated: 2020-09-18T09:27:41Z file_id: '19577' file_name: Kersting & Geierhos (2020c), Kersting2020c.pdf file_size: 963370 relation: main_file success: 1 file_date_updated: 2020-09-18T09:27:41Z has_accepted_license: '1' keyword: - Customer Reviews - Sentiment Analysis - Online Labour Markets language: - iso: eng page: 263--272 place: Setúbal, Portugal project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods publisher: SCITEPRESS status: public title: What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers type: conference user_id: '58701' year: '2020' ... --- _id: '8312' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Geierhos M. Requirements Engineering in OTF-Computing. In: Encyclopedia.Pub. Basel, Switzerland: MDPI; 2019.' apa: 'Bäumer, F. S., & Geierhos, M. (2019). Requirements Engineering in OTF-Computing. In encyclopedia.pub. Basel, Switzerland: MDPI.' bibtex: '@inbook{Bäumer_Geierhos_2019, place={Basel, Switzerland}, title={Requirements Engineering in OTF-Computing}, booktitle={encyclopedia.pub}, publisher={MDPI}, author={Bäumer, Frederik Simon and Geierhos, Michaela}, year={2019} }' chicago: 'Bäumer, Frederik Simon, and Michaela Geierhos. “Requirements Engineering in OTF-Computing.” In Encyclopedia.Pub. Basel, Switzerland: MDPI, 2019.' ieee: 'F. S. Bäumer and M. Geierhos, “Requirements Engineering in OTF-Computing,” in encyclopedia.pub, Basel, Switzerland: MDPI, 2019.' mla: Bäumer, Frederik Simon, and Michaela Geierhos. “Requirements Engineering in OTF-Computing.” Encyclopedia.Pub, MDPI, 2019. short: 'F.S. Bäumer, M. Geierhos, in: Encyclopedia.Pub, MDPI, Basel, Switzerland, 2019.' date_created: 2019-03-05T08:54:37Z date_updated: 2022-01-06T07:03:53Z department: - _id: '36' - _id: '1' - _id: '579' keyword: - OTF Computing - Natural Language Processing - Requirements Engineering language: - iso: eng main_file_link: - open_access: '1' url: https://encyclopedia.pub/131 oa: '1' place: Basel, Switzerland project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: encyclopedia.pub publication_status: published publisher: MDPI quality_controlled: '1' status: public title: Requirements Engineering in OTF-Computing type: encyclopedia_article user_id: '42496' year: '2019' ... --- _id: '8424' abstract: - lang: eng text: 'The vision of On-the-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language. Since non-technical users write their software requirements themselves and in unrestricted natural language, deficits occur such as inaccuracy and incompleteness. These deficits are usually met by natural language processing methods, which have to face special challenges in OTF Computing because maximum automation is the goal. In this paper, we present current automatic approaches for solving inaccuracies and incompletenesses in natural language requirement descriptions and elaborate open challenges. In particular, we will discuss the necessity of domain-specific resources and show why, despite far-reaching automation, an intelligent and guided integration of end users into the compensation process is required. In this context, we present our idea of a chat bot that integrates users into the compensation process depending on the given circumstances. ' article_number: '22' article_type: original author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Kersting J, Geierhos M. Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches. Computers. 2019;8(1). doi:10.3390/computers8010022' apa: 'Bäumer, F. S., Kersting, J., & Geierhos, M. (2019). Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches. Computers, 8(1). https://doi.org/10.3390/computers8010022' bibtex: '@article{Bäumer_Kersting_Geierhos_2019, title={Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches}, volume={8}, DOI={10.3390/computers8010022}, number={122}, journal={Computers}, publisher={MDPI AG, Basel, Switzerland}, author={Bäumer, Frederik Simon and Kersting, Joschka and Geierhos, Michaela}, year={2019} }' chicago: 'Bäumer, Frederik Simon, Joschka Kersting, and Michaela Geierhos. “Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches.” Computers 8, no. 1 (2019). https://doi.org/10.3390/computers8010022.' ieee: 'F. S. Bäumer, J. Kersting, and M. Geierhos, “Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches,” Computers, vol. 8, no. 1, 2019.' mla: 'Bäumer, Frederik Simon, et al. “Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches.” Computers, vol. 8, no. 1, 22, MDPI AG, Basel, Switzerland, 2019, doi:10.3390/computers8010022.' short: F.S. Bäumer, J. Kersting, M. Geierhos, Computers 8 (2019). conference: end_date: 2018-10-06 location: Vilnius, Lithuania name: 24th International Conference on Information and Software Technologies (ICIST 2018) start_date: 2018-10-04 date_created: 2019-03-06T14:27:28Z date_updated: 2022-01-06T07:03:55Z ddc: - '000' department: - _id: '36' - _id: '1' - _id: '579' doi: 10.3390/computers8010022 file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:23:34Z date_updated: 2020-09-18T09:23:34Z file_id: '19572' file_name: Bäumer et al. (2019), Baeumer2019.pdf file_size: 3164523 relation: main_file success: 1 file_date_updated: 2020-09-18T09:23:34Z has_accepted_license: '1' intvolume: ' 8' issue: '1' keyword: - Inaccuracy Detection - Natural Language Software Requirements - Chat Bot language: - iso: eng main_file_link: - open_access: '1' url: https://www.mdpi.com/2073-431X/8/1/22/pdf oa: '1' project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: Computers publication_identifier: issn: - 2073-431X publication_status: published publisher: MDPI AG, Basel, Switzerland quality_controlled: '1' status: public title: 'Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches' type: journal_article user_id: '58701' volume: 8 year: '2019' ... --- _id: '8529' author: - first_name: Nina full_name: Seemann, Nina id: '65408' last_name: Seemann - first_name: Marie-Luis full_name: Merten, Marie-Luis last_name: Merten citation: ama: 'Seemann N, Merten M-L. UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte. In: Sahle P, ed. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Frankfurt am Main, Germany: Zenodo; 2019:352-353. doi:10.5281/ZENODO.2596094' apa: 'Seemann, N., & Merten, M.-L. (2019). UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte. In P. Sahle (Ed.), DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts (pp. 352–353). Frankfurt am Main, Germany: Zenodo. https://doi.org/10.5281/ZENODO.2596094' bibtex: '@inproceedings{Seemann_Merten_2019, place={Frankfurt am Main, Germany}, title={UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte}, DOI={10.5281/ZENODO.2596094}, booktitle={DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts}, publisher={Zenodo}, author={Seemann, Nina and Merten, Marie-Luis}, editor={Sahle, PatrickEditor}, year={2019}, pages={352–353} }' chicago: 'Seemann, Nina, and Marie-Luis Merten. “UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte.” In DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, edited by Patrick Sahle, 352–53. Frankfurt am Main, Germany: Zenodo, 2019. https://doi.org/10.5281/ZENODO.2596094.' ieee: 'N. Seemann and M.-L. Merten, “UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte,” in DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, Mainz and Frankfurt am Main, Germany, 2019, pp. 352–353.' mla: 'Seemann, Nina, and Marie-Luis Merten. “UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte.” DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, edited by Patrick Sahle, Zenodo, 2019, pp. 352–53, doi:10.5281/ZENODO.2596094.' short: 'N. Seemann, M.-L. Merten, in: P. Sahle (Ed.), DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, Zenodo, Frankfurt am Main, Germany, 2019, pp. 352–353.' conference: end_date: 2019-03-29 location: Mainz and Frankfurt am Main, Germany name: 'DHd 2019 Digital Humanities: multimedial & multimodal.' start_date: 2019-03-25 date_created: 2019-03-21T08:39:17Z date_updated: 2022-01-06T07:03:56Z department: - _id: '36' - _id: '1' - _id: '579' doi: 10.5281/ZENODO.2596094 editor: - first_name: Patrick full_name: Sahle, Patrick last_name: Sahle language: - iso: ger main_file_link: - open_access: '1' url: https://zenodo.org/record/2596095/files/2019_DHd_BookOfAbstracts_web.pdf?download=1 oa: '1' page: 352-353 place: Frankfurt am Main, Germany project: - _id: '39' name: InterGramm publication: 'DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts' publication_identifier: isbn: - 978-3-00-062166-6 publication_status: published publisher: Zenodo status: public title: 'UPB-Annotate: Ein maßgeschneidertes Toolkit für historische Texte' type: conference_abstract user_id: '13929' year: '2019' ... --- _id: '8532' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Bianca full_name: Buff, Bianca last_name: Buff - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Buff B, Geierhos M. Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen. In: Sahle P, ed. DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts. Frankfurt am Main, Germany: Zenodo; 2019:192-193. doi:10.5281/zenodo.2596095' apa: 'Bäumer, F. S., Buff, B., & Geierhos, M. (2019). Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen. In P. Sahle (Ed.), DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts (pp. 192–193). Frankfurt am Main, Germany: Zenodo. https://doi.org/10.5281/zenodo.2596095' bibtex: '@inproceedings{Bäumer_Buff_Geierhos_2019, place={Frankfurt am Main, Germany}, title={Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen}, DOI={10.5281/zenodo.2596095}, booktitle={DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts}, publisher={Zenodo}, author={Bäumer, Frederik Simon and Buff, Bianca and Geierhos, Michaela}, editor={Sahle, PatrickEditor}, year={2019}, pages={192–193} }' chicago: 'Bäumer, Frederik Simon, Bianca Buff, and Michaela Geierhos. “Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen.” In DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, edited by Patrick Sahle, 192–93. Frankfurt am Main, Germany: Zenodo, 2019. https://doi.org/10.5281/zenodo.2596095.' ieee: 'F. S. Bäumer, B. Buff, and M. Geierhos, “Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen,” in DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, Mainz and Frankfurt am Main, Germany, 2019, pp. 192–193.' mla: 'Bäumer, Frederik Simon, et al. “Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen.” DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, edited by Patrick Sahle, Zenodo, 2019, pp. 192–93, doi:10.5281/zenodo.2596095.' short: 'F.S. Bäumer, B. Buff, M. Geierhos, in: P. Sahle (Ed.), DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts, Zenodo, Frankfurt am Main, Germany, 2019, pp. 192–193.' conference: end_date: 2019-03-29 location: Mainz and Frankfurt am Main, Germany name: 'DHd 2019 Digital Humanities: multimedial & multimodal.' start_date: 2019-03-25 date_created: 2019-03-21T09:02:37Z date_updated: 2022-01-06T07:03:56Z department: - _id: '36' - _id: '1' - _id: '579' doi: 10.5281/zenodo.2596095 editor: - first_name: Patrick full_name: Sahle, Patrick last_name: Sahle language: - iso: ger main_file_link: - open_access: '1' url: https://zenodo.org/record/2596095/files/2019_DHd_BookOfAbstracts_web.pdf?download=1 oa: '1' page: 192-193 place: Frankfurt am Main, Germany publication: 'DHd 2019 Digital Humanities: multimedial & multimodal. Konferenzabstracts' publication_identifier: isbn: - 978-3-00-062166-6 publication_status: published publisher: Zenodo status: public title: Potentielle Privatsphäreverletzungen aufdecken und automatisiert sichtbar machen type: conference_abstract user_id: '13929' year: '2019' ... --- _id: '9613' abstract: - lang: eng text: The ability to openly evaluate products, locations and services is an achievement of the Web 2.0. It has never been easier to inform oneself about the quality of products or services and possible alternatives. Forming one’s own opinion based on the impressions of other people can lead to better experiences. However, this presupposes trust in one’s fellows as well as in the quality of the review platforms. In previous work on physician reviews and the corresponding websites, it was observed that there occurs faulty behavior by some reviewers and there were noteworthy differences in the technical implementation of the portals and in the efforts of site operators to maintain high quality reviews. These experiences raise new questions regarding what trust means on review platforms, how trust arises and how easily it can be destroyed. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Bäumer FS, Geierhos M. In Reviews We Trust: But Should We? Experiences with Physician Review Websites. In: Ramachandran M, Walters R, Wills G, Méndez Muñoz V, Chang V, eds. Proceedings of the 4th International Conference on Internet of Things, Big Data and Security. Setúbal, Portugal: SCITEPRESS; 2019:147-155.' apa: 'Kersting, J., Bäumer, F. S., & Geierhos, M. (2019). In Reviews We Trust: But Should We? Experiences with Physician Review Websites. In M. Ramachandran, R. Walters, G. Wills, V. Méndez Muñoz, & V. Chang (Eds.), Proceedings of the 4th International Conference on Internet of Things, Big Data and Security (pp. 147–155). Setúbal, Portugal: SCITEPRESS.' bibtex: '@inproceedings{Kersting_Bäumer_Geierhos_2019, place={Setúbal, Portugal}, title={In Reviews We Trust: But Should We? Experiences with Physician Review Websites}, booktitle={Proceedings of the 4th International Conference on Internet of Things, Big Data and Security}, publisher={SCITEPRESS}, author={Kersting, Joschka and Bäumer, Frederik Simon and Geierhos, Michaela}, editor={Ramachandran, Muthu and Walters, Robert and Wills, Gary and Méndez Muñoz, Víctor and Chang, VictorEditors}, year={2019}, pages={147–155} }' chicago: 'Kersting, Joschka, Frederik Simon Bäumer, and Michaela Geierhos. “In Reviews We Trust: But Should We? Experiences with Physician Review Websites.” In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, edited by Muthu Ramachandran, Robert Walters, Gary Wills, Víctor Méndez Muñoz, and Victor Chang, 147–55. Setúbal, Portugal: SCITEPRESS, 2019.' ieee: 'J. Kersting, F. S. Bäumer, and M. Geierhos, “In Reviews We Trust: But Should We? Experiences with Physician Review Websites,” in Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, Heraklion, Greece, 2019, pp. 147–155.' mla: 'Kersting, Joschka, et al. “In Reviews We Trust: But Should We? Experiences with Physician Review Websites.” Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, edited by Muthu Ramachandran et al., SCITEPRESS, 2019, pp. 147–55.' short: 'J. Kersting, F.S. Bäumer, M. Geierhos, in: M. Ramachandran, R. Walters, G. Wills, V. Méndez Muñoz, V. Chang (Eds.), Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, SCITEPRESS, Setúbal, Portugal, 2019, pp. 147–155.' conference: end_date: 2019-05-04 location: Heraklion, Greece name: 4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2019) start_date: 2019-05-02 date_created: 2019-05-06T09:00:48Z date_updated: 2022-01-06T07:04:17Z ddc: - '000' department: - _id: '1' - _id: '579' editor: - first_name: Muthu full_name: Ramachandran, Muthu last_name: Ramachandran - first_name: Robert full_name: Walters, Robert last_name: Walters - first_name: Gary full_name: Wills, Gary last_name: Wills - first_name: Víctor full_name: Méndez Muñoz, Víctor last_name: Méndez Muñoz - first_name: Victor full_name: Chang, Victor last_name: Chang file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:24:41Z date_updated: 2020-09-18T09:24:41Z file_id: '19573' file_name: Kersting et al. (2019), Kersting2019.pdf file_size: 1112502 relation: main_file success: 1 file_date_updated: 2020-09-18T09:24:41Z has_accepted_license: '1' keyword: - Trust - Physician Reviews - Network Analysis language: - iso: eng main_file_link: - url: www.insticc.org/Primoris/Resources/PaperPdf.ashx?idPaper=77454 page: 147-155 place: Setúbal, Portugal publication: Proceedings of the 4th International Conference on Internet of Things, Big Data and Security publication_identifier: isbn: - 978-989-758-369-8 unknown: - 2184-4976 publication_status: published publisher: SCITEPRESS quality_controlled: '1' status: public title: 'In Reviews We Trust: But Should We? Experiences with Physician Review Websites' type: conference user_id: '58701' year: '2019' ... --- _id: '12946' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Bianca full_name: Buff, Bianca last_name: Buff citation: ama: 'Bäumer FS, Buff B. How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness. In: Proceedings of the 8th International Conference on Data Science, Technology and Applications. ; 2019. doi:10.5220/0007828301290136' apa: Bäumer, F. S., & Buff, B. (2019). How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness. In Proceedings of the 8th International Conference on Data Science, Technology and Applications. https://doi.org/10.5220/0007828301290136 bibtex: '@inproceedings{Bäumer_Buff_2019, title={How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness}, DOI={10.5220/0007828301290136}, booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications}, author={Bäumer, Frederik Simon and Buff, Bianca}, year={2019} }' chicago: Bäumer, Frederik Simon, and Bianca Buff. “How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness.” In Proceedings of the 8th International Conference on Data Science, Technology and Applications, 2019. https://doi.org/10.5220/0007828301290136. ieee: F. S. Bäumer and B. Buff, “How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness,” in Proceedings of the 8th International Conference on Data Science, Technology and Applications, 2019. mla: Bäumer, Frederik Simon, and Bianca Buff. “How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness.” Proceedings of the 8th International Conference on Data Science, Technology and Applications, 2019, doi:10.5220/0007828301290136. short: 'F.S. Bäumer, B. Buff, in: Proceedings of the 8th International Conference on Data Science, Technology and Applications, 2019.' date_created: 2019-08-19T08:26:42Z date_updated: 2022-01-06T06:51:27Z department: - _id: '579' - _id: '1' doi: 10.5220/0007828301290136 language: - iso: eng publication: Proceedings of the 8th International Conference on Data Science, Technology and Applications publication_identifier: isbn: - '9789897583773' publication_status: published status: public title: How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness type: conference user_id: '38837' year: '2019' ...