--- _id: '45882' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer - first_name: Wei-Fan full_name: Chen, Wei-Fan id: '82920' last_name: Chen - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Henning full_name: Wachsmuth, Henning last_name: Wachsmuth citation: ama: 'Bäumer FS, Chen W-F, Geierhos M, Kersting J, Wachsmuth H. Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:65-84. doi:10.5281/zenodo.8068456' apa: Bäumer, F. S., Chen, W.-F., Geierhos, M., Kersting, J., & Wachsmuth, H. (2023). Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 65–84). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068456 bibtex: '@inbook{Bäumer_Chen_Geierhos_Kersting_Wachsmuth_2023, place={Paderborn}, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation}, volume={412}, DOI={10.5281/zenodo.8068456}, booktitle={On-The-Fly Computing -- Individualized IT-services in dynamic markets}, publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Bäumer, Frederik Simon and Chen, Wei-Fan and Geierhos, Michaela and Kersting, Joschka and Wachsmuth, Henning}, editor={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, pages={65–84}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }' chicago: 'Bäumer, Frederik Simon, Wei-Fan Chen, Michaela Geierhos, Joschka Kersting, and Henning Wachsmuth. “Dialogue-Based Requirement Compensation and Style-Adjusted Data-to-Text Generation.” In On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:65–84. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.5281/zenodo.8068456.' ieee: 'F. S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, and H. Wachsmuth, “Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84.' mla: Bäumer, Frederik Simon, et al. “Dialogue-Based Requirement Compensation and Style-Adjusted Data-to-Text Generation.” On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol. 412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84, doi:10.5281/zenodo.8068456. short: 'F.S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, H. Wachsmuth, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 65–84.' date_created: 2023-07-07T07:29:13Z date_updated: 2023-07-07T11:20:52Z ddc: - '004' department: - _id: '7' - _id: '369' doi: 10.5281/zenodo.8068456 editor: - first_name: Claus-Jochen full_name: Haake, Claus-Jochen last_name: Haake - first_name: Friedhelm full_name: Meyer auf der Heide, Friedhelm last_name: Meyer auf der Heide - first_name: Marco full_name: Platzner, Marco last_name: Platzner - first_name: Henning full_name: Wachsmuth, Henning last_name: Wachsmuth - first_name: Heike full_name: Wehrheim, Heike last_name: Wehrheim file: - access_level: open_access content_type: application/pdf creator: florida date_created: 2023-07-07T07:28:58Z date_updated: 2023-07-07T11:20:52Z file_id: '45883' file_name: B1-Chapter-SFB-Buch-Final.pdf file_size: 1342718 relation: main_file file_date_updated: 2023-07-07T11:20:52Z has_accepted_license: '1' intvolume: ' 412' language: - iso: eng oa: '1' page: 65-84 place: Paderborn 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: On-The-Fly Computing -- Individualized IT-services in dynamic markets publisher: Heinz Nixdorf Institut, Universität Paderborn series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts status: public title: Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation type: book_chapter user_id: '477' volume: 412 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: '45863' abstract: - lang: eng text: "In the proposal for our CRC in 2011, we formulated a vision of markets for\r\nIT services that describes an approach to the provision of such services\r\nthat was novel at that time and, to a large extent, remains so today:\r\n„Our vision of on-the-fly computing is that of IT services individually and\r\nautomatically configured and brought to execution from flexibly combinable\r\nservices traded on markets. At the same time, we aim at organizing\r\nmarkets whose participants maintain a lively market of services through\r\nappropriate entrepreneurial actions.“\r\nOver the last 12 years, we have developed methods and techniques to\r\naddress problems critical to the convenient, efficient, and secure use of\r\non-the-fly computing. Among other things, we have made the description\r\nof services more convenient by allowing natural language input,\r\nincreased the quality of configured services through (natural language)\r\ninteraction and more efficient configuration processes and analysis\r\nprocedures, made the quality of (the products of) providers in the\r\nmarketplace transparent through reputation systems, and increased the\r\nresource efficiency of execution through reconfigurable heterogeneous\r\ncomputing nodes and an integrated treatment of service description and\r\nconfiguration. We have also developed network infrastructures that have\r\na high degree of adaptivity, scalability, efficiency, and reliability, and\r\nprovide cryptographic guarantees of anonymity and security for market\r\nparticipants and their products and services.\r\nTo demonstrate the pervasiveness of the OTF computing approach, we\r\nhave implemented a proof-of-concept for OTF computing that can run\r\ntypical scenarios of an OTF market. We illustrated the approach using\r\na cutting-edge application scenario – automated machine learning (AutoML).\r\nFinally, we have been pushing our work for the perpetuation of\r\nOn-The-Fly Computing beyond the SFB and sharing the expertise gained\r\nin the SFB in events with industry partners as well as transfer projects.\r\nThis work required a broad spectrum of expertise. Computer scientists\r\nand economists with research interests such as computer networks and\r\ndistributed algorithms, security and cryptography, software engineering\r\nand verification, configuration and machine learning, computer engineering\r\nand HPC, microeconomics and game theory, business informatics\r\nand management have successfully collaborated here." alternative_title: - Collaborative Research Centre 901 (2011 – 2023) author: - first_name: Claus-Jochen full_name: Haake, Claus-Jochen id: '20801' last_name: Haake - first_name: Friedhelm full_name: Meyer auf der Heide, Friedhelm id: '15523' last_name: Meyer auf der Heide - first_name: Marco full_name: Platzner, Marco id: '398' last_name: Platzner - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth - first_name: Heike full_name: Wehrheim, Heike id: '573' last_name: Wehrheim citation: ama: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Heinz Nixdorf Institut, Universität Paderborn; 2023. doi:10.17619/UNIPB/1-1797 apa: Haake, C.-J., Meyer auf der Heide, F., Platzner, M., Wachsmuth, H., & Wehrheim, H. (2023). On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.17619/UNIPB/1-1797 bibtex: '@book{Haake_Meyer auf der Heide_Platzner_Wachsmuth_Wehrheim_2023, place={Paderborn}, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={On-The-Fly Computing -- Individualized IT-services in dynamic markets}, volume={412}, DOI={10.17619/UNIPB/1-1797}, publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }' chicago: 'Haake, Claus-Jochen, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol. 412. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.17619/UNIPB/1-1797.' ieee: 'C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023.' mla: Haake, Claus-Jochen, et al. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Heinz Nixdorf Institut, Universität Paderborn, 2023, doi:10.17619/UNIPB/1-1797. short: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim, On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023. date_created: 2023-07-05T07:16:51Z date_updated: 2023-08-29T06:44:36Z ddc: - '000' department: - _id: '7' doi: 10.17619/UNIPB/1-1797 file: - access_level: open_access content_type: application/pdf creator: ups date_created: 2023-07-05T07:15:55Z date_updated: 2023-07-05T07:19:14Z file_id: '45864' file_name: SFB-Buch-Final.pdf file_size: 15480050 relation: main_file file_date_updated: 2023-07-05T07:19:14Z has_accepted_license: '1' intvolume: ' 412' language: - iso: eng oa: '1' page: '247' place: Paderborn project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' - _id: '2' name: 'SFB 901 - A: SFB 901 - Project Area A' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '4' name: 'SFB 901 - C: SFB 901 - Project Area C' - _id: '82' name: 'SFB 901 - T: SFB 901 - Project Area T' - _id: '5' grant_number: '160364472' name: 'SFB 901 - A1: SFB 901 - Möglichkeiten und Grenzen lokaler Strategien in dynamischen Netzen (Subproject A1)' - _id: '7' grant_number: '160364472' name: 'SFB 901 - A3: SFB 901 - Der Markt für Services: Anreize, Algorithmen, Implementation (Subproject A3)' - _id: '8' grant_number: '160364472' name: 'SFB 901 - A4: SFB 901 - Empirische Analysen in Märkten für OTF Dienstleistungen (Subproject A4)' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _id: '10' grant_number: '160364472' name: 'SFB 901 - B2: Konfiguration und Bewertung (B02)' - _id: '11' name: 'SFB 901 - B3: SFB 901 - Subproject B3' - _id: '12' name: 'SFB 901 - B4: SFB 901 - Subproject B4' - _id: '13' name: 'SFB 901 - C1: SFB 901 - Subproject C1' - _id: '14' grant_number: '160364472' name: 'SFB 901 - C2: SFB 901 - On-The-Fly Compute Centers I: Heterogene Ausführungsumgebungen (Subproject C2)' - _id: '16' grant_number: '160364472' name: 'SFB 901 - C4: SFB 901 - On-The-Fly Compute Centers II: Ausführung komponierter Dienste in konfigurierbaren Rechenzentren (Subproject C4)' - _id: '17' name: 'SFB 901 - C5: SFB 901 - Subproject C5' - _id: '83' name: 'SFB 901 - T1: SFB 901 -Subproject T1' - _id: '84' name: 'SFB 901 - T2: SFB 901 -Subproject T2' publication_identifier: unknown: - 978-3-947647-31-6 publisher: Heinz Nixdorf Institut, Universität Paderborn series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts status: public title: On-The-Fly Computing -- Individualized IT-services in dynamic markets type: book user_id: '477' volume: 412 year: '2023' ... --- _id: '33274' author: - first_name: Wei-Fan full_name: Chen, Wei-Fan id: '82920' last_name: Chen - first_name: Mei-Hua full_name: Chen, Mei-Hua last_name: Chen - first_name: Garima full_name: Mudgal, Garima last_name: Mudgal - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Chen W-F, Chen M-H, Mudgal G, Wachsmuth H. Analyzing Culture-Specific Argument Structures in Learner Essays. In: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022). ; 2022:51-61.' apa: Chen, W.-F., Chen, M.-H., Mudgal, G., & Wachsmuth, H. (2022). Analyzing Culture-Specific Argument Structures in Learner Essays. Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 51–61. bibtex: '@inproceedings{Chen_Chen_Mudgal_Wachsmuth_2022, title={Analyzing Culture-Specific Argument Structures in Learner Essays}, booktitle={Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022)}, author={Chen, Wei-Fan and Chen, Mei-Hua and Mudgal, Garima and Wachsmuth, Henning}, year={2022}, pages={51–61} }' chicago: Chen, Wei-Fan, Mei-Hua Chen, Garima Mudgal, and Henning Wachsmuth. “Analyzing Culture-Specific Argument Structures in Learner Essays.” In Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 51–61, 2022. ieee: W.-F. Chen, M.-H. Chen, G. Mudgal, and H. Wachsmuth, “Analyzing Culture-Specific Argument Structures in Learner Essays,” in Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61. mla: Chen, Wei-Fan, et al. “Analyzing Culture-Specific Argument Structures in Learner Essays.” Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61. short: 'W.-F. Chen, M.-H. Chen, G. Mudgal, H. Wachsmuth, in: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.' date_created: 2022-09-06T13:51:23Z date_updated: 2022-11-18T09:56:17Z department: - _id: '600' language: - iso: eng page: 51 - 61 project: - _id: '9' name: 'SFB 901 - B1: SFB 901 - Subproject B1' - _id: '1' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' publication: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022) status: public title: Analyzing Culture-Specific Argument Structures in Learner Essays type: conference user_id: '477' year: '2022' ... --- _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: '31054' abstract: - lang: eng text: This paper aims at discussing past limitations set in sentiment analysis research regarding explicit and implicit mentions of opinions. Previous studies have regularly neglected this question in favor of methodical research on standard-datasets. Furthermore, they were limited to linguistically less-diverse domains, such as commercial product reviews. We face this issue by annotating a German-language physician review dataset that contains numerous implicit, long, and complex statements that indicate aspect ratings, such as the physician’s friendliness. We discuss the nature of implicit statements and present various samples to illustrate the challenge described. 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. Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis. In: Kersting J, ed. Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications. IARIA; 2022:5-9.' apa: 'Kersting, J., & Bäumer, F. S. (2022). Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis. In J. Kersting (Ed.), Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications (pp. 5–9). IARIA.' bibtex: '@inproceedings{Kersting_Bäumer_2022, place={Barcelona, Spain}, title={Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis}, booktitle={Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications}, publisher={IARIA}, author={Kersting, Joschka and Bäumer, Frederik Simon}, editor={Kersting, Joschka}, year={2022}, pages={5–9} }' chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis.” In Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, edited by Joschka Kersting, 5–9. Barcelona, Spain: IARIA, 2022.' ieee: 'J. Kersting and F. S. Bäumer, “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis,” in Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, Barcelona, Spain, 2022, pp. 5–9.' mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis.” Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, edited by Joschka Kersting, IARIA, 2022, pp. 5–9.' short: 'J. Kersting, F.S. Bäumer, in: J. Kersting (Ed.), Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, IARIA, Barcelona, Spain, 2022, pp. 5–9.' conference: location: Barcelona, Spain name: The Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022) start_date: 2022-03 date_created: 2022-05-04T08:12:09Z date_updated: 2022-12-01T13:40:11Z ddc: - '006' editor: - first_name: Joschka full_name: Kersting, Joschka last_name: Kersting file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2022-12-01T13:39:48Z date_updated: 2022-12-01T13:39:48Z file_id: '34172' file_name: Kersting & Bäumer (2022), Kersting2022.pdf file_size: 155548 relation: main_file success: 1 file_date_updated: 2022-12-01T13:39:48Z has_accepted_license: '1' keyword: - Sentiment analysis - Natural language processing - Aspect phrase extraction language: - iso: eng page: 5-9 place: Barcelona, Spain 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: 'Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications' publication_status: published publisher: IARIA status: public title: 'Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis' type: conference user_id: '58701' year: '2022' ... --- _id: '31068' author: - first_name: Mei-Hua full_name: Chen, Mei-Hua last_name: Chen - first_name: Garima full_name: Mudgal, Garima last_name: Mudgal - first_name: Wei-Fan full_name: Chen, Wei-Fan id: '82920' last_name: Chen - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Chen M-H, Mudgal G, Chen W-F, Wachsmuth H. Investigating the argumentation structures of EFL learners from diverse language backgrounds. In: EUROCALL. ; 2022.' apa: Chen, M.-H., Mudgal, G., Chen, W.-F., & Wachsmuth, H. (2022). Investigating the argumentation structures of EFL learners from diverse language backgrounds. EUROCALL. bibtex: '@inproceedings{Chen_Mudgal_Chen_Wachsmuth_2022, title={Investigating the argumentation structures of EFL learners from diverse language backgrounds}, booktitle={EUROCALL}, author={Chen, Mei-Hua and Mudgal, Garima and Chen, Wei-Fan and Wachsmuth, Henning}, year={2022} }' chicago: Chen, Mei-Hua, Garima Mudgal, Wei-Fan Chen, and Henning Wachsmuth. “Investigating the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.” In EUROCALL, 2022. ieee: M.-H. Chen, G. Mudgal, W.-F. Chen, and H. Wachsmuth, “Investigating the argumentation structures of EFL learners from diverse language backgrounds,” 2022. mla: Chen, Mei-Hua, et al. “Investigating the Argumentation Structures of EFL Learners from Diverse Language Backgrounds.” EUROCALL, 2022. short: 'M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.' date_created: 2022-05-05T07:50:21Z date_updated: 2022-05-09T14:58:39Z department: - _id: '600' language: - iso: eng 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: EUROCALL status: public title: Investigating the argumentation structures of EFL learners from diverse language backgrounds type: conference_abstract user_id: '82920' year: '2022' ... --- _id: '26049' abstract: - lang: eng text: 'Content is the new oil. Users consume billions of terabytes a day while surfing on news sites or blogs, posting on social media sites, and sending chat messages around the globe. While content is heterogeneous, the dominant form of web content is text. There are situations where more diversity needs to be introduced into text content, for example, to reuse it on websites or to allow a chatbot to base its models on the information conveyed rather than of the language used. In order to achieve this, paraphrasing techniques have been developed: One example is Text spinning, a technique that automatically paraphrases text while leaving the intent intact. This makes it easier to reuse content, or to change the language generated by the bot more human. One method for modifying texts is a combination of translation and back-translation. This paper presents NATTS, a naive approach that uses transformer-based translation models to create diversified text, combining translation steps in one model. An advantage of this approach is that it can be fine-tuned and handle technical language.' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon last_name: Bäumer - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Sergej full_name: Denisov, Sergej last_name: Denisov - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Kersting J, Denisov S, Geierhos M. IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021. IADIS; 2021:221--225.' apa: 'Bäumer, F. S., Kersting, J., Denisov, S., & Geierhos, M. (2021). IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225.' bibtex: '@inproceedings{Bäumer_Kersting_Denisov_Geierhos_2021, title={IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING}, booktitle={PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021}, publisher={IADIS}, author={Bäumer, Frederik Simon and Kersting, Joschka and Denisov, Sergej and Geierhos, Michaela}, year={2021}, pages={221--225} }' chicago: 'Bäumer, Frederik Simon, Joschka Kersting, Sergej Denisov, and Michaela Geierhos. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.” In PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225. IADIS, 2021.' ieee: 'F. S. Bäumer, J. Kersting, S. Denisov, and M. Geierhos, “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, Lisbon, Portugal, 2021, pp. 221--225.' mla: 'Bäumer, Frederik Simon, et al. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.” PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, IADIS, 2021, pp. 221--225.' short: 'F.S. Bäumer, J. Kersting, S. Denisov, M. Geierhos, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, IADIS, 2021, pp. 221--225.' conference: end_date: 15.10.2021 location: Lisbon, Portugal name: 18th International Conference on Applied Computing start_date: 13.10.2021 date_created: 2021-10-11T15:26:58Z date_updated: 2022-01-06T06:57:16Z ddc: - '000' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2021-10-15T15:54:41Z date_updated: 2021-10-15T15:54:41Z file_id: '26282' file_name: Bäumer et al. (2021), Baeumer2021.pdf file_size: 411667 relation: main_file success: 1 file_date_updated: 2021-10-15T15:54:41Z has_accepted_license: '1' keyword: - Software Requirements - Natural Language Processing - Transfer Learning - On-The-Fly Computing language: - iso: eng page: 221--225 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 CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021 publisher: IADIS status: public title: 'IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING' type: conference user_id: '58701' year: '2021' ... --- _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: '21178' abstract: - lang: eng text: "When engaging in argumentative discourse, skilled human debaters tailor\r\nclaims to the beliefs of the audience, to construct effective arguments.\r\nRecently, the field of computational argumentation witnessed extensive effort\r\nto address the automatic generation of arguments. However, existing approaches\r\ndo not perform any audience-specific adaptation. In this work, we aim to bridge\r\nthis gap by studying the task of belief-based claim generation: Given a\r\ncontroversial topic and a set of beliefs, generate an argumentative claim\r\ntailored to the beliefs. To tackle this task, we model the people's prior\r\nbeliefs through their stances on controversial topics and extend\r\nstate-of-the-art text generation models to generate claims conditioned on the\r\nbeliefs. Our automatic evaluation confirms the ability of our approach to adapt\r\nclaims to a set of given beliefs. In a manual study, we additionally evaluate\r\nthe generated claims in terms of informativeness and their likelihood to be\r\nuttered by someone with a respective belief. Our results reveal the limitations\r\nof modeling users' beliefs based on their stances, but demonstrate the\r\npotential of encoding beliefs into argumentative texts, laying the ground for\r\nfuture exploration of audience reach." author: - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Wei-Fan full_name: Chen, Wei-Fan id: '82920' last_name: Chen - first_name: Timon full_name: Gurcke, Timon id: '52174' last_name: Gurcke - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Alshomary M, Chen W-F, Gurcke T, Wachsmuth H. Belief-based Generation of Argumentative Claims. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics; 2021:224-223.' apa: 'Alshomary, M., Chen, W.-F., Gurcke, T., & Wachsmuth, H. (2021). Belief-based Generation of Argumentative Claims. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 224–223.' bibtex: '@inproceedings{Alshomary_Chen_Gurcke_Wachsmuth_2021, title={Belief-based Generation of Argumentative Claims}, booktitle={Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume}, publisher={Association for Computational Linguistics}, author={Alshomary, Milad and Chen, Wei-Fan and Gurcke, Timon and Wachsmuth, Henning}, year={2021}, pages={224–223} }' chicago: 'Alshomary, Milad, Wei-Fan Chen, Timon Gurcke, and Henning Wachsmuth. “Belief-Based Generation of Argumentative Claims.” In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 224–223. Association for Computational Linguistics, 2021.' ieee: 'M. Alshomary, W.-F. Chen, T. Gurcke, and H. Wachsmuth, “Belief-based Generation of Argumentative Claims,” in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Online, 2021, pp. 224–223.' mla: 'Alshomary, Milad, et al. “Belief-Based Generation of Argumentative Claims.” Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Association for Computational Linguistics, 2021, pp. 224–223.' short: 'M. Alshomary, W.-F. Chen, T. Gurcke, H. Wachsmuth, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Association for Computational Linguistics, 2021, pp. 224–223.' conference: location: Online name: 'Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume' date_created: 2021-02-05T08:00:07Z date_updated: 2022-05-09T15:01:53Z department: - _id: '600' language: - iso: eng main_file_link: - url: https://www.aclweb.org/anthology/2021.eacl-main.17 page: 224-223 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: 'Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume' publisher: Association for Computational Linguistics status: public title: Belief-based Generation of Argumentative Claims type: conference user_id: '82920' year: '2021' ... --- _id: '23709' author: - first_name: Wei-Fan full_name: Chen, Wei-Fan id: '82920' last_name: Chen - first_name: Khalid full_name: Al Khatib, Khalid last_name: Al Khatib - first_name: Benno full_name: Stein, Benno last_name: Stein - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Chen W-F, Al Khatib K, Stein B, Wachsmuth H. Controlled Neural Sentence-Level Reframing of News Articles. In: Findings of the Association for Computational Linguistics: EMNLP 2021. ; 2021:2683-2693.' apa: 'Chen, W.-F., Al Khatib, K., Stein, B., & Wachsmuth, H. (2021). Controlled Neural Sentence-Level Reframing of News Articles. Findings of the Association for Computational Linguistics: EMNLP 2021, 2683–2693.' bibtex: '@inproceedings{Chen_Al Khatib_Stein_Wachsmuth_2021, title={Controlled Neural Sentence-Level Reframing of News Articles}, booktitle={Findings of the Association for Computational Linguistics: EMNLP 2021}, author={Chen, Wei-Fan and Al Khatib, Khalid and Stein, Benno and Wachsmuth, Henning}, year={2021}, pages={2683–2693} }' chicago: 'Chen, Wei-Fan, Khalid Al Khatib, Benno Stein, and Henning Wachsmuth. “Controlled Neural Sentence-Level Reframing of News Articles.” In Findings of the Association for Computational Linguistics: EMNLP 2021, 2683–93, 2021.' ieee: 'W.-F. Chen, K. Al Khatib, B. Stein, and H. Wachsmuth, “Controlled Neural Sentence-Level Reframing of News Articles,” in Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.' mla: 'Chen, Wei-Fan, et al. “Controlled Neural Sentence-Level Reframing of News Articles.” Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–93.' short: 'W.-F. Chen, K. Al Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.' date_created: 2021-09-02T20:09:20Z date_updated: 2022-05-09T15:00:09Z department: - _id: '600' language: - iso: eng main_file_link: - url: https://aclanthology.org/2021.findings-emnlp.228.pdf page: 2683 - 2693 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: 'Findings of the Association for Computational Linguistics: EMNLP 2021' status: public title: Controlled Neural Sentence-Level Reframing of News Articles type: conference user_id: '82920' year: '2021' ... --- _id: '22229' author: - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Shahbaz full_name: Syed, Shahbaz last_name: Syed - first_name: Martin full_name: Potthast, Martin last_name: Potthast - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Alshomary M, Syed S, Potthast M, Wachsmuth H. Argument Undermining: Counter-Argument Generation by Attacking Weak Premises. In: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics; 2021:1816–1827. doi:10.18653/v1/2021.findings-acl.159' apa: 'Alshomary, M., Syed, S., Potthast, M., & Wachsmuth, H. (2021). Argument Undermining: Counter-Argument Generation by Attacking Weak Premises. Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 1816–1827. https://doi.org/10.18653/v1/2021.findings-acl.159' bibtex: '@inproceedings{Alshomary_Syed_Potthast_Wachsmuth_2021, series={Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021}, title={Argument Undermining: Counter-Argument Generation by Attacking Weak Premises}, DOI={10.18653/v1/2021.findings-acl.159}, booktitle={Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)}, publisher={Association for Computational Linguistics}, author={Alshomary, Milad and Syed, Shahbaz and Potthast, Martin and Wachsmuth, Henning}, year={2021}, pages={1816–1827}, collection={Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021} }' chicago: 'Alshomary, Milad, Shahbaz Syed, Martin Potthast, and Henning Wachsmuth. “Argument Undermining: Counter-Argument Generation by Attacking Weak Premises.” In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 1816–1827. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Association for Computational Linguistics, 2021. https://doi.org/10.18653/v1/2021.findings-acl.159.' ieee: 'M. Alshomary, S. Syed, M. Potthast, and H. Wachsmuth, “Argument Undermining: Counter-Argument Generation by Attacking Weak Premises,” in Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Online, 2021, pp. 1816–1827, doi: 10.18653/v1/2021.findings-acl.159.' mla: 'Alshomary, Milad, et al. “Argument Undermining: Counter-Argument Generation by Attacking Weak Premises.” Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association for Computational Linguistics, 2021, pp. 1816–1827, doi:10.18653/v1/2021.findings-acl.159.' short: 'M. Alshomary, S. Syed, M. Potthast, H. Wachsmuth, in: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association for Computational Linguistics, 2021, pp. 1816–1827.' conference: location: Online name: The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) date_created: 2021-05-26T07:06:18Z date_updated: 2022-05-09T15:06:36Z department: - _id: '600' doi: 10.18653/v1/2021.findings-acl.159 language: - iso: eng main_file_link: - url: https://aclanthology.org/2021.findings-acl.159.pdf page: 1816–1827 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: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) publisher: Association for Computational Linguistics series_title: 'Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021' status: public title: 'Argument Undermining: Counter-Argument Generation by Attacking Weak Premises' type: conference user_id: '82920' 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: '15025' abstract: - lang: eng text: In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available. author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Lorijn full_name: van Rooijen, Lorijn id: '58843' last_name: van Rooijen - first_name: Heiko full_name: Hamann, Heiko last_name: Hamann citation: ama: Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation. 2020;28(2):165–193. doi:10.1162/evco_a_00266 apa: Wever, M. D., van Rooijen, L., & Hamann, H. (2020). Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation, 28(2), 165–193. https://doi.org/10.1162/evco_a_00266 bibtex: '@article{Wever_van Rooijen_Hamann_2020, title={Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}, volume={28}, DOI={10.1162/evco_a_00266}, number={2}, journal={Evolutionary Computation}, publisher={MIT Press Journals}, author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}, year={2020}, pages={165–193} }' chicago: 'Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation 28, no. 2 (2020): 165–193. https://doi.org/10.1162/evco_a_00266.' ieee: 'M. D. Wever, L. van Rooijen, and H. Hamann, “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets,” Evolutionary Computation, vol. 28, no. 2, pp. 165–193, 2020, doi: 10.1162/evco_a_00266.' mla: Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation, vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:10.1162/evco_a_00266. short: M.D. Wever, L. van Rooijen, H. Hamann, Evolutionary Computation 28 (2020) 165–193. date_created: 2019-11-18T14:19:19Z date_updated: 2022-01-06T06:52:15Z department: - _id: '34' - _id: '355' - _id: '26' - _id: '63' - _id: '238' doi: 10.1162/evco_a_00266 intvolume: ' 28' issue: '2' language: - iso: eng page: 165–193 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Evolutionary Computation publication_status: published publisher: MIT Press Journals related_material: link: - relation: confirmation url: https://www.mitpressjournals.org/doi/pdf/10.1162/evco_a_00266 status: public title: Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets type: journal_article user_id: '15415' volume: 28 year: '2020' ...