--- _id: '44323' abstract: - lang: eng text: "Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods.\r\nImplicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit\r\n(3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified?\r\nThe uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights.\r\nAs a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain." author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting citation: ama: Kersting J. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München ; 2023. apa: Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München . bibtex: '@book{Kersting_2023, place={Neubiberg}, title={Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}, publisher={Universität der Bundeswehr München }, author={Kersting, Joschka}, year={2023} }' chicago: 'Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' ieee: 'J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' mla: Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München , 2023. short: J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023. date_created: 2023-05-02T12:54:00Z date_updated: 2023-07-03T12:29:50Z department: - _id: '579' - _id: '7' language: - iso: ger page: '208' place: Neubiberg project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Subproject B1' publication_status: published publisher: 'Universität der Bundeswehr München ' related_material: link: - relation: supplementary_material url: https://athene-forschung.unibw.de/145003 status: public supervisor: - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 title: Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining type: dissertation user_id: '58701' year: '2023' ... --- _id: '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: '29000' abstract: - lang: eng text: "This thesis aims to provide a bidirectional chatbot solution for the requirement engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide the composition of software service On-the-Fly (OTF). The sub-project (B1) of the SFB 901 project deals with the parameters of service configuration. OTF Computing aims to eradicate the dependency on the requirement engineers for the software development process. However, there is no existing bidirectional chatbot solution that analyses user software requirements and provides viable suggestions to the user regarding their service. Previously, CORDULA chatbot was developed to analyze the software requirements but cannot keep the conversation’s context. The Rasa framework is integrated with the knowledge base to solve the issue, the knowledge base provides domain-specific knowledge to the chatbot. The software description is passed through the natural language understanding process to give consciousness to the chatbot. This process involves various machine learning models, including app family classification, to correctly identify the domain for user OTF service. The statistical models like naïve Bayes, kNN and SVM are compared with transformer models for this classification task. Furthermore, the entities (functional requirements) are also separated from the user description.\r\nThe chatbot provides the suggestion of requirements from the preliminary service template with the support of the knowledge base. Furthermore, the generated response is compared with the state-of-the-art DialoGPT transformer model and ChatterBot conversational library. These models are trained over the software development related conversational dataset. All the responses are ranked using the DialoRPT model, and the BLEU score to evaluates the models’ responses. Moreover, the chatbot mod- els are tested with human participants, they used and scored the chatbot responses based on effectiveness, efficiency and satisfaction. The overall response accuracy is also measured by averaging the user approval over the generated responses." author: - first_name: Mobeen full_name: Ahmed, Mobeen last_name: Ahmed citation: ama: Ahmed M. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing.; 2022. apa: Ahmed, M. (2022). Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing. bibtex: '@book{Ahmed_2022, title={Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing}, author={Ahmed, Mobeen}, year={2022} }' chicago: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing, 2022. ieee: M. Ahmed, Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing. 2022. mla: Ahmed, Mobeen. Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing. 2022. short: M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing, 2022. date_created: 2021-12-16T15:13:07Z date_updated: 2023-05-02T13:25:45Z ddc: - '004' department: - _id: '600' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2023-05-02T13:25:27Z date_updated: 2023-05-02T13:25:27Z file_id: '44325' file_name: Thesis-Report-MOBEEN-AHMED-6856465-Knowledge_Base_Enhanced___User_centric_Dialogue_Design_for_OTFComputing.pdf file_size: 3092211 relation: main_file success: 1 file_date_updated: 2023-05-02T13:25:27Z has_accepted_license: '1' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication_status: published status: public supervisor: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting title: Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing type: mastersthesis user_id: '58701' year: '2022' ... --- _id: '45790' author: - first_name: Juela full_name: Palushi, Juela last_name: Palushi citation: ama: Palushi J. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks.; 2022. apa: Palushi, J. (2022). Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks. bibtex: '@book{Palushi_2022, title={Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks}, author={Palushi, Juela}, year={2022} }' chicago: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022. ieee: J. Palushi, Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks. 2022. mla: Palushi, Juela. Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks. 2022. short: J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022. date_created: 2023-06-27T12:57:57Z date_updated: 2023-07-05T07:31:17Z department: - _id: '600' language: - iso: eng project: - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _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' status: public supervisor: - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth title: Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks type: bachelorsthesis user_id: '477' year: '2022' ... --- _id: '45789' author: - first_name: Vinaykumar full_name: Budanurmath, Vinaykumar last_name: Budanurmath citation: ama: Budanurmath V. Propaganda Technique Detection Using Connotation Frames.; 2022. apa: Budanurmath, V. (2022). Propaganda Technique Detection Using Connotation Frames. bibtex: '@book{Budanurmath_2022, title={Propaganda Technique Detection Using Connotation Frames}, author={Budanurmath, Vinaykumar}, year={2022} }' chicago: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation Frames, 2022. ieee: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames. 2022. mla: Budanurmath, Vinaykumar. Propaganda Technique Detection Using Connotation Frames. 2022. short: V. Budanurmath, Propaganda Technique Detection Using Connotation Frames, 2022. date_created: 2023-06-27T12:56:04Z date_updated: 2023-07-05T07:33:45Z department: - _id: '600' language: - iso: eng project: - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _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' status: public supervisor: - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth title: Propaganda Technique Detection Using Connotation Frames type: mastersthesis user_id: '477' 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: '45788' author: - first_name: Jonas full_name: Bülling, Jonas last_name: Bülling citation: ama: 'Bülling J. Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump.; 2021.' apa: 'Bülling, J. (2021). Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump.' bibtex: '@book{Bülling_2021, title={Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump}, author={Bülling, Jonas}, year={2021} }' chicago: 'Bülling, Jonas. Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump, 2021.' ieee: 'J. Bülling, Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump. 2021.' mla: 'Bülling, Jonas. Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump. 2021.' short: 'J. Bülling, Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump, 2021.' date_created: 2023-06-27T12:54:30Z date_updated: 2023-07-05T07:32:18Z department: - _id: '600' language: - iso: eng project: - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _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' status: public supervisor: - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth title: 'Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump' type: mastersthesis user_id: '477' year: '2021' ... --- _id: '45787' author: - first_name: Avishek full_name: Mishra, Avishek last_name: Mishra citation: ama: Mishra A. Computational Text Professionalization Using Neural Sequence-to-Sequence Models.; 2021. apa: Mishra, A. (2021). Computational Text Professionalization using Neural Sequence-to-Sequence Models. bibtex: '@book{Mishra_2021, title={Computational Text Professionalization using Neural Sequence-to-Sequence Models}, author={Mishra, Avishek}, year={2021} }' chicago: Mishra, Avishek. Computational Text Professionalization Using Neural Sequence-to-Sequence Models, 2021. ieee: A. Mishra, Computational Text Professionalization using Neural Sequence-to-Sequence Models. 2021. mla: Mishra, Avishek. Computational Text Professionalization Using Neural Sequence-to-Sequence Models. 2021. short: A. Mishra, Computational Text Professionalization Using Neural Sequence-to-Sequence Models, 2021. date_created: 2023-06-27T12:51:08Z date_updated: 2023-07-05T07:32:50Z department: - _id: '600' language: - iso: eng project: - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' - _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' status: public supervisor: - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth title: Computational Text Professionalization using Neural Sequence-to-Sequence Models type: mastersthesis user_id: '477' year: '2021' ...