[{"date_created":"2023-05-02T12:54:00Z","project":[{"grant_number":"160364472","name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - B1: SFB 901 - Subproject B1","grant_number":"160364472"}],"status":"public","publication_status":"published","department":[{"_id":"579"},{"_id":"7"}],"publisher":"Universität der Bundeswehr München ","author":[{"last_name":"Kersting","id":"58701","first_name":"Joschka","full_name":"Kersting, Joschka"}],"user_id":"58701","related_material":{"link":[{"url":"https://athene-forschung.unibw.de/145003","relation":"supplementary_material"}]},"title":"Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining","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."}],"place":"Neubiberg","language":[{"iso":"ger"}],"supervisor":[{"orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela","id":"42496","last_name":"Geierhos"}],"page":"208","type":"dissertation","year":"2023","citation":{"chicago":"Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.","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 .","mla":"Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München , 2023.","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} }","short":"J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023.","ieee":"J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023."},"date_updated":"2023-07-03T12:29:50Z","_id":"44323"},{"intvolume":" 1860","_id":"46205","page":"45-65","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","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.","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} }","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.","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."},"year":"2023","type":"book_chapter","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."}],"ddc":["004"],"user_id":"58701","publication":"Data Management Technologies and Applications","file_date_updated":"2023-07-28T15:10:48Z","publisher":"Springer Nature Switzerland","author":[{"first_name":"Joschka","full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701"},{"last_name":"Geierhos","id":"42496","first_name":"Michaela","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela"}],"file":[{"relation":"main_file","success":1,"date_updated":"2023-07-28T15:10:48Z","content_type":"application/pdf","creator":"jkers","file_id":"46207","file_size":746336,"access_level":"closed","file_name":"Kersting and Geierhos (2023), Kersting2023b.pdf","date_created":"2023-07-28T15:10:48Z"}],"volume":1860,"date_created":"2023-07-28T15:03:14Z","has_accepted_license":"1","status":"public","date_updated":"2023-07-28T15:11:10Z","doi":"10.1007/978-3-031-37890-4_3","series_title":"Communications in Computer and Information Science","language":[{"iso":"eng"}],"place":"Cham","title":"Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews","department":[{"_id":"579"}],"publication_identifier":{"isbn":["9783031378898","9783031378904"],"issn":["1865-0929","1865-0937"]},"publication_status":"published","editor":[{"last_name":"Cuzzocrea","first_name":"Alfredo","full_name":"Cuzzocrea, Alfredo"},{"first_name":"Oleg","full_name":"Gusikhin, Oleg","last_name":"Gusikhin"},{"first_name":"Slimane","full_name":"Hammoudi, Slimane","last_name":"Hammoudi"},{"last_name":"Quix","full_name":"Quix, Christoph","first_name":"Christoph"}],"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"}]},{"abstract":[{"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.","lang":"eng"}],"user_id":"58701","ddc":["004"],"file":[{"creator":"jkers","file_id":"34150","file_size":1153017,"success":1,"relation":"main_file","content_type":"application/pdf","date_updated":"2022-11-28T13:21:32Z","date_created":"2022-11-28T13:21:32Z","file_name":"Kersting et al. (2022), Kersting2022.pdf","access_level":"closed"}],"publisher":"Springer International Publishing","author":[{"id":"58701","last_name":"Kersting","full_name":"Kersting, Joschka","first_name":"Joschka"},{"first_name":"Mobeen","full_name":"Ahmed, Mobeen","last_name":"Ahmed"},{"id":"42496","last_name":"Geierhos","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela"}],"publication":"HCI International 2022 Posters","file_date_updated":"2022-11-28T13:21:32Z","keyword":["On-The-Fly Computing","Chatbot","Knowledge Base"],"status":"public","has_accepted_license":"1","date_created":"2022-06-27T09:27:06Z","volume":1580,"intvolume":" 1580","_id":"32179","conference":{"location":"Virtual","name":"24th International Conference on Human-Computer Interaction (HCII 2022)","start_date":"2022-06-26","end_date":"2022-07-01"},"type":"book_chapter","year":"2022","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","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.","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.","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)} }","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.","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."},"page":"419--426","place":"Cham, Switzerland","related_material":{"link":[{"relation":"confirmation","url":"https://link.springer.com/chapter/10.1007/978-3-031-06417-3_56"}]},"title":"Chatbot-Enhanced Requirements Resolution for Automated Service Compositions","department":[{"_id":"579"}],"project":[{"name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - B1: SFB 901 - Subproject B1","_id":"9"}],"editor":[{"full_name":"Stephanidis, Constantine","first_name":"Constantine","last_name":"Stephanidis"},{"full_name":"Antona, Margherita","first_name":"Margherita","last_name":"Antona"},{"full_name":"Ntoa, Stavroula","first_name":"Stavroula","last_name":"Ntoa"}],"publication_identifier":{"isbn":["9783031064166","9783031064173"],"issn":["1865-0929","1865-0937"]},"publication_status":"published","date_updated":"2022-11-28T13:22:16Z","doi":"10.1007/978-3-031-06417-3_56","series_title":"Communications in Computer and Information Science (CCIS)","language":[{"iso":"eng"}]},{"type":"book_chapter","citation":{"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.","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)} }","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","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.","short":"J. Kersting, M. Geierhos, in: R. Loukanova (Ed.), Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, Springer, Cham, 2021, pp. 163--189."},"year":"2021","page":"163--189 ","_id":"17905","intvolume":" 939","status":"public","has_accepted_license":"1","date_created":"2020-08-13T09:29:52Z","volume":939,"file":[{"file_size":512065,"file_id":"21594","creator":"jkers","content_type":"application/pdf","date_updated":"2021-04-08T08:14:05Z","success":1,"relation":"main_file","file_name":"Kersting-Geierhos2021_Chapter_TowardsAspectExtractionAndClas.pdf","date_created":"2021-04-08T08:14:05Z","access_level":"closed"}],"publisher":"Springer","author":[{"full_name":"Kersting, Joschka","first_name":"Joschka","id":"58701","last_name":"Kersting"},{"orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela","id":"42496","last_name":"Geierhos"}],"publication":"Natural Language Processing in Artificial Intelligence -- NLPinAI 2020","file_date_updated":"2021-04-08T08:14:05Z","user_id":"58701","ddc":["000"],"abstract":[{"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. ","lang":"eng"}],"language":[{"iso":"eng"}],"series_title":"Studies in Computational Intelligence (SCI)","doi":"10.1007/978-3-030-63787-3_6","date_updated":"2022-01-06T06:53:23Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"editor":[{"full_name":"Loukanova, Roussanka","first_name":"Roussanka","last_name":"Loukanova"}],"publication_identifier":{"unknown":["978-3-030-63786-6 ; 978-3-030-63787-3"]},"publication_status":"published","department":[{"_id":"579"}],"title":"Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks","place":"Cham"},{"publication_status":"published","date_created":"2021-05-07T16:27:27Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"status":"public","publication":"Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021)","department":[{"_id":"579"}],"publisher":"SCITEPRESS","author":[{"first_name":"Joschka","full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701"},{"orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela","id":"42496","last_name":"Geierhos"}],"title":"Well-being in Plastic Surgery: Deep Learning Reveals Patients' Evaluations","user_id":"58701","place":"Online","page":"275--284","citation":{"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.","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.","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.","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.","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."},"type":"conference","year":"2021","language":[{"iso":"eng"}],"conference":{"name":"10th International Conference on Data Science, Technology and Applications (DATA 2021)","start_date":"2021-07-06","location":"Online","end_date":"2021-07-08"},"date_updated":"2022-01-06T06:55:23Z","_id":"22051"},{"department":[{"_id":"579"}],"editor":[{"last_name":"Kapetanios","full_name":"Kapetanios, Epaminondas","first_name":"Epaminondas"},{"first_name":"Helmut","full_name":"Horacek, Helmut","last_name":"Horacek"},{"first_name":"Elisabeth","full_name":"Métais, Elisabeth","last_name":"Métais"},{"last_name":"Meziane","first_name":"Farid","full_name":"Meziane, Farid"}],"publication_status":"published","project":[{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"place":"Saarbrücken, Germany","title":"Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting","series_title":"Lecture Notes in Computer Science","language":[{"iso":"eng"}],"date_updated":"2022-07-14T08:00:56Z","publisher":"Springer","author":[{"first_name":"Joschka","full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701"},{"last_name":"Geierhos","id":"42496","first_name":"Michaela","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela"}],"publication":"Natural Language Processing and Information Systems","file_date_updated":"2022-07-14T08:00:35Z","file":[{"file_size":506329,"creator":"jkers","file_id":"32362","date_updated":"2022-07-14T08:00:35Z","content_type":"application/pdf","success":1,"relation":"main_file","date_created":"2022-07-14T08:00:35Z","file_name":"Kersting & Geierhos (2021b), Kersting2021b.pdf","access_level":"closed"}],"volume":12801,"status":"public","has_accepted_license":"1","date_created":"2021-05-07T16:31:05Z","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."}],"ddc":["004"],"user_id":"58701","year":"2021","type":"book_chapter","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.","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.","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.","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} }","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.","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."},"page":"231--242","intvolume":" 12801","_id":"22052","conference":{"name":"26th International Conference on Natural Language & Information Systems (NLDB 2021)","start_date":"2021-06-23","location":"Saarbrücken, Germany","end_date":"2021-06-25"}},{"page":"368--382","type":"book_chapter","year":"2020","citation":{"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.","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","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","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.","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} }","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.","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."},"conference":{"start_date":"2020-10-15","name":"26th International Conference on Information and Software Technologies (ICIST 2020)","location":"Kaunas, Litauen","end_date":"2020-10-17"},"_id":"17347","intvolume":" 1283","date_created":"2020-06-26T14:23:52Z","has_accepted_license":"1","status":"public","volume":1283,"file":[{"file_size":599881,"file_id":"20309","creator":"jkers","content_type":"application/pdf","date_updated":"2020-11-07T19:47:30Z","relation":"main_file","success":1,"file_name":"Bäumer et al. (2020), Baeumer2020.pdf .pdf","date_created":"2020-11-07T19:47:30Z","access_level":"closed"}],"publication":"Information and Software Technologies","file_date_updated":"2020-11-07T19:47:30Z","author":[{"full_name":"Bäumer, Frederik Simon","first_name":"Frederik Simon","id":"38837","last_name":"Bäumer"},{"full_name":"Kersting, Joschka","first_name":"Joschka","id":"58701","last_name":"Kersting"},{"last_name":"Buff","full_name":"Buff, Bianca","first_name":"Bianca"},{"last_name":"Geierhos","id":"42496","first_name":"Michaela","full_name":"Geierhos, Michaela","orcid":"0000-0002-8180-5606"}],"publisher":"Springer","user_id":"58701","ddc":["004"],"abstract":[{"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.","lang":"eng"}],"language":[{"iso":"eng"}],"series_title":"Communications in Computer and Information Science","doi":"https://doi.org/10.1007/978-3-030-59506-7_30","date_updated":"2022-01-06T06:53:08Z","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"publication_status":"published","editor":[{"last_name":"Audrius","first_name":"Lopata","full_name":"Audrius, Lopata"},{"full_name":"Rita, Butkienė","first_name":"Butkienė","last_name":"Rita"},{"last_name":"Daina","full_name":"Daina, Gudonienė","first_name":"Gudonienė"},{"last_name":"Vilma","first_name":"Sukackė","full_name":"Vilma, Sukackė"}],"department":[{"_id":"579"},{"_id":"1"},{"_id":"36"}],"title":"Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P2P News Tagging"},{"department":[{"_id":"579"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"title":"SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:53:51Z","file":[{"file_size":1064877,"file_id":"20443","creator":"jkers","date_updated":"2020-11-19T17:29:03Z","content_type":"application/pdf","relation":"main_file","success":1,"date_created":"2020-11-19T17:29:03Z","file_name":"Kersting & Bäumer (2020), Kersting2020d.pdf","access_level":"closed"}],"keyword":["Software Requirements","Natural Language Processing","Transfer Learning","On-The-Fly Computing"],"publication":"PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020","file_date_updated":"2020-11-19T17:29:03Z","publisher":"IADIS","author":[{"id":"58701","last_name":"Kersting","full_name":"Kersting, Joschka","first_name":"Joschka"},{"full_name":"Bäumer, Frederik Simon","first_name":"Frederik Simon","id":"38837","last_name":"Bäumer"}],"date_created":"2020-08-31T10:59:54Z","has_accepted_license":"1","status":"public","user_id":"58701","ddc":["000"],"page":"119--123","year":"2020","type":"conference","citation":{"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} }","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.","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.","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.","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","start_date":"18.11.2020","name":"17th International Conference on Applied Computing"},"_id":"18686"},{"citation":{"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.","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.","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.","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} }","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.","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.","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."},"year":"2020","type":"conference","page":"391--400","_id":"15580","conference":{"location":"Valetta, Malta","name":"International Conference on Agents and Artificial Intelligence (ICAART) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI)"},"file":[{"access_level":"closed","file_name":"Kersting & Geierhos (2020), Kersting2020.pdf","date_created":"2020-09-18T09:27:00Z","content_type":"application/pdf","date_updated":"2020-09-18T09:27:00Z","relation":"main_file","success":1,"file_size":421780,"creator":"jkers","file_id":"19576"}],"author":[{"first_name":"Joschka","full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701"},{"id":"42496","last_name":"Geierhos","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela"}],"publisher":"SCITEPRESS","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)","keyword":["Deep Learning","Natural Language Processing","Aspect-based Sentiment Analysis"],"file_date_updated":"2020-09-18T09:27:00Z","status":"public","has_accepted_license":"1","date_created":"2020-01-15T08:35:07Z","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."}],"user_id":"58701","ddc":["000"],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:52:29Z","department":[{"_id":"579"}],"project":[{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"place":"Setúbal, Portugal","title":"Aspect Phrase Extraction in Sentiment Analysis with Deep Learning"},{"_id":"15582","conference":{"location":"Valetta, Malta","name":"International Conference on Pattern Recognition Applications and Methods (ICPRAM)"},"type":"conference","year":"2020","citation":{"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.","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.","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.","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.","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.","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} }"},"page":"630--637","abstract":[{"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.","lang":"eng"}],"user_id":"58701","ddc":["000"],"file":[{"access_level":"closed","file_name":"Buff et al. (2020), Buff2020.pdf","date_created":"2020-09-18T09:25:30Z","relation":"main_file","success":1,"date_updated":"2020-09-18T09:25:30Z","content_type":"application/pdf","creator":"jkers","file_id":"19574","file_size":287956}],"publisher":"SCITEPRESS","author":[{"first_name":"Bianca","full_name":"Buff, Bianca","last_name":"Buff"},{"id":"58701","last_name":"Kersting","full_name":"Kersting, Joschka","first_name":"Joschka"},{"first_name":"Michaela","full_name":"Geierhos, Michaela","orcid":"0000-0002-8180-5606","last_name":"Geierhos","id":"42496"}],"file_date_updated":"2020-09-18T09:25:30Z","publication":"Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020)","keyword":["Identity Disclosure","Privacy Protection","Physician Review Website","De-Anonymization","Medical Domain"],"status":"public","has_accepted_license":"1","date_created":"2020-01-15T08:49:25Z","date_updated":"2022-01-06T06:52:30Z","language":[{"iso":"eng"}],"place":"Setúbal, Portugal","title":"Detection of Privacy Disclosure in the Medical Domain: A Survey","department":[{"_id":"579"}],"project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - Subproject B1"}]},{"project":[{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"9","name":"SFB 901 - Subproject B1"},{"_id":"1","name":"SFB 901"}],"department":[{"_id":"579"}],"title":"Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis","place":"North Miami Beach, FL, USA","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:52:31Z","date_created":"2020-01-24T09:10:09Z","status":"public","has_accepted_license":"1","file":[{"relation":"main_file","success":1,"content_type":"application/pdf","date_updated":"2020-09-18T09:39:08Z","creator":"jkers","file_id":"19582","file_size":464976,"access_level":"closed","date_created":"2020-09-18T09:39:08Z","file_name":"Kersting & Geierhos (2020b), Kersting2020b.pdf"}],"publication":"Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference","file_date_updated":"2020-09-18T09:39:08Z","author":[{"id":"58701","last_name":"Kersting","full_name":"Kersting, Joschka","first_name":"Joschka"},{"last_name":"Geierhos","id":"42496","first_name":"Michaela","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela"}],"publisher":"AAAI","user_id":"58701","ddc":["000"],"page":"282--285","type":"conference","year":"2020","citation":{"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.","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} }","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.","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."},"conference":{"end_date":"2020-05-20","location":"North Miami Beach, FL, USA","start_date":"2020-05-17","name":"The 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference"},"_id":"15635"},{"department":[{"_id":"579"}],"project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"place":"Setúbal, Portugal","title":"What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:52:19Z","file":[{"file_size":963370,"creator":"jkers","file_id":"19577","content_type":"application/pdf","date_updated":"2020-09-18T09:27:41Z","success":1,"relation":"main_file","file_name":"Kersting & Geierhos (2020c), Kersting2020c.pdf","date_created":"2020-09-18T09:27:41Z","access_level":"closed"}],"publisher":"SCITEPRESS","author":[{"first_name":"Joschka","full_name":"Kersting, Joschka","last_name":"Kersting","id":"58701"},{"id":"42496","last_name":"Geierhos","full_name":"Geierhos, Michaela","orcid":"0000-0002-8180-5606","first_name":"Michaela"}],"publication":"Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods","keyword":["Customer Reviews","Sentiment Analysis","Online Labour Markets"],"file_date_updated":"2020-09-18T09:27:41Z","status":"public","has_accepted_license":"1","date_created":"2019-12-06T13:09:42Z","abstract":[{"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.","lang":"eng"}],"user_id":"58701","ddc":["000"],"type":"conference","year":"2020","citation":{"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.","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.","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.","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.","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.","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} }","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."},"page":"263--272","_id":"15256","conference":{"name":"International Conference on Pattern Recognition Applications and Methods (ICPRAM)","location":"Valetta, Malta"}},{"language":[{"iso":"eng"}],"oa":"1","date_updated":"2022-01-06T07:03:53Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B1","_id":"9"}],"publication_status":"published","department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"title":"Requirements Engineering in OTF-Computing","place":"Basel, Switzerland","year":"2019","type":"encyclopedia_article","citation":{"short":"F.S. Bäumer, M. Geierhos, in: Encyclopedia.Pub, MDPI, Basel, Switzerland, 2019.","ieee":"F. S. Bäumer and M. Geierhos, “Requirements Engineering in OTF-Computing,” in encyclopedia.pub, Basel, Switzerland: MDPI, 2019.","chicago":"Bäumer, Frederik Simon, and Michaela Geierhos. “Requirements Engineering in OTF-Computing.” In Encyclopedia.Pub. Basel, Switzerland: MDPI, 2019.","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. 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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. 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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} }","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.","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.","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.","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.","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."},"main_file_link":[{"url":"www.insticc.org/Primoris/Resources/PaperPdf.ashx?idPaper=77454"}],"conference":{"end_date":"2019-05-04","start_date":"2019-05-02","name":"4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2019)","location":"Heraklion, Greece"},"_id":"9613","date_created":"2019-05-06T09:00:48Z","has_accepted_license":"1","status":"public","file":[{"content_type":"application/pdf","date_updated":"2020-09-18T09:24:41Z","success":1,"relation":"main_file","file_size":1112502,"file_id":"19573","creator":"jkers","access_level":"closed","file_name":"Kersting et al. 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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."}],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T07:04:17Z","publication_identifier":{"isbn":["978-989-758-369-8"],"unknown":["2184-4976"]},"publication_status":"published","editor":[{"last_name":"Ramachandran","full_name":"Ramachandran, Muthu","first_name":"Muthu"},{"last_name":"Walters","first_name":"Robert","full_name":"Walters, Robert"},{"last_name":"Wills","first_name":"Gary","full_name":"Wills, Gary"},{"full_name":"Méndez Muñoz, Víctor","first_name":"Víctor","last_name":"Méndez Muñoz"},{"last_name":"Chang","first_name":"Victor","full_name":"Chang, Victor"}],"department":[{"_id":"1"},{"_id":"579"}],"title":"In Reviews We Trust: But Should We? 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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."},"year":"2019","type":"conference","language":[{"iso":"eng"}],"doi":"10.5220/0007828301290136","_id":"12946","date_updated":"2022-01-06T06:51:27Z"},{"_id":"13435","date_updated":"2022-01-06T06:51:36Z","year":"2019","citation":{"ieee":"E. Friesen, Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn, 2019.","short":"E. Friesen, Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis, Universität Paderborn, 2019.","mla":"Friesen, Edwin. Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn, 2019.","bibtex":"@book{Friesen_2019, title={Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis}, publisher={Universität Paderborn}, author={Friesen, Edwin}, year={2019} }","apa":"Friesen, E. (2019). Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn.","ama":"Friesen E. Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn; 2019.","chicago":"Friesen, Edwin. Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn, 2019."},"type":"bachelorsthesis","language":[{"iso":"ger"}],"supervisor":[{"last_name":"Hüllermeier","id":"48129","first_name":"Eyke","full_name":"Hüllermeier, Eyke"},{"id":"42496","last_name":"Geierhos","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","first_name":"Michaela"}],"title":"Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis","user_id":"477","department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"publisher":"Universität Paderborn","author":[{"last_name":"Friesen","full_name":"Friesen, Edwin","first_name":"Edwin"}],"project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"date_created":"2019-09-20T14:58:49Z","status":"public"},{"title":"How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges","place":"Cham, Switzerland","project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"9","name":"SFB 901 - Subproject B1"}],"publication_identifier":{"isbn":["978-3-319-91946-1"]},"publication_status":"published","editor":[{"full_name":"Silberztein, Max ","first_name":"Max ","last_name":"Silberztein"},{"first_name":"Faten ","full_name":"Atigui, Faten ","last_name":"Atigui"},{"full_name":"Kornyshova, Elena ","first_name":"Elena ","last_name":"Kornyshova"},{"first_name":"Elisabeth ","full_name":"Métais, Elisabeth ","last_name":"Métais"},{"full_name":"Meziane, Farid ","first_name":"Farid ","last_name":"Meziane"}],"department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"doi":"10.1007/978-3-319-91947-8_53","date_updated":"2022-01-06T06:55:47Z","language":[{"iso":"eng"}],"series_title":"Lecture Notes in Computer Science","user_id":"477","ddc":["000"],"abstract":[{"lang":"eng","text":"The vision of On-The-Fly Computing is an automatic composition\r\nof existing software services. Based on natural language software\r\ndescriptions, end users will receive compositions tailored to their needs.\r\nFor this reason, the quality of the initial software service description\r\nstrongly determines whether a software composition really meets the expectations\r\nof end users. In this paper, we expose open NLP challenges\r\nneeded to be faced for service composition in On-The-Fly Computing."}],"date_created":"2018-04-13T08:54:56Z","status":"public","has_accepted_license":"1","volume":10859,"file":[{"file_id":"5326","creator":"ups","file_size":327508,"relation":"main_file","success":1,"content_type":"application/pdf","date_updated":"2018-11-02T16:12:26Z","file_name":"Bäumer-Geierhos2018_Chapter_HowToDealWithInaccurateService.pdf","date_created":"2018-11-02T16:12:26Z","access_level":"closed"}],"publication":"Proceedings of the 23rd International Conference on Natural Language and Information Systems","keyword":["Requirements Extraction","Temporal Reordering of Software Functions","Inaccuracy Compensation"],"file_date_updated":"2018-11-02T16:12:26Z","author":[{"id":"38837","last_name":"Bäumer","full_name":"Bäumer, Frederik Simon","first_name":"Frederik Simon"},{"first_name":"Michaela","orcid":"0000-0002-8180-5606","full_name":"Geierhos, Michaela","last_name":"Geierhos","id":"42496"}],"publisher":"Springer","quality_controlled":"1","conference":{"start_date":"2018-06-13","name":"23rd International Conference on Natural Language and Information Systems","location":"Paris, France","end_date":"2018-06-18"},"_id":"2322","intvolume":" 10859","page":"509-513","year":"2018","type":"book_chapter","citation":{"short":"F.S. Bäumer, M. Geierhos, in: M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, F. Meziane (Eds.), Proceedings of the 23rd International Conference on Natural Language and Information Systems, Springer, Cham, Switzerland, 2018, pp. 509–513.","ieee":"F. S. Bäumer and M. Geierhos, “How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges,” in Proceedings of the 23rd International Conference on Natural Language and Information Systems, vol. 10859, M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, and F. Meziane, Eds. Cham, Switzerland: Springer, 2018, pp. 509–513.","ama":"Bäumer FS, Geierhos M. How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In: Silberztein M, Atigui F, Kornyshova E, Métais E, Meziane F, eds. Proceedings of the 23rd International Conference on Natural Language and Information Systems. Vol 10859. Lecture Notes in Computer Science. Cham, Switzerland: Springer; 2018:509-513. doi:10.1007/978-3-319-91947-8_53","apa":"Bäumer, F. S., & Geierhos, M. (2018). How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, & F. Meziane (Eds.), Proceedings of the 23rd International Conference on Natural Language and Information Systems (Vol. 10859, pp. 509–513). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-91947-8_53","chicago":"Bäumer, Frederik Simon, and Michaela Geierhos. “How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges.” In Proceedings of the 23rd International Conference on Natural Language and Information Systems, edited by Max Silberztein, Faten Atigui, Elena Kornyshova, Elisabeth Métais, and Farid Meziane, 10859:509–13. Lecture Notes in Computer Science. Cham, Switzerland: Springer, 2018. https://doi.org/10.1007/978-3-319-91947-8_53.","bibtex":"@inbook{Bäumer_Geierhos_2018, place={Cham, Switzerland}, series={Lecture Notes in Computer Science}, title={How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges}, volume={10859}, DOI={10.1007/978-3-319-91947-8_53}, booktitle={Proceedings of the 23rd International Conference on Natural Language and Information Systems}, publisher={Springer}, author={Bäumer, Frederik Simon and Geierhos, Michaela}, editor={Silberztein, Max and Atigui, Faten and Kornyshova, Elena and Métais, Elisabeth and Meziane, Farid Editors}, year={2018}, pages={509–513}, collection={Lecture Notes in Computer Science} }","mla":"Bäumer, Frederik Simon, and Michaela Geierhos. “How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges.” Proceedings of the 23rd International Conference on Natural Language and Information Systems, edited by Max Silberztein et al., vol. 10859, Springer, 2018, pp. 509–13, doi:10.1007/978-3-319-91947-8_53."}}]