Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München .
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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 
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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 
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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 
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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.
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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 
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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.
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Chen, M.-H., Mudgal, G., Chen, W.-F., &; Wachsmuth, H. (2022). Investigating the argumentation structures of EFL learners from diverse language backgrounds. EUROCALL.
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Ahmed, M. (2022). Knowledge Base Enhanced &; User-centric Dialogue Design for OTF Computing.
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Palushi, J. (2022). Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks.
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Budanurmath, V. (2022). Propaganda Technique Detection Using Connotation Frames.
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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.
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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 
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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.
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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.
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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.
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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.
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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 
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DOI: 10.18653/v1/2021.findings-acl.159

Bülling, J. (2021). Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump.
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Mishra, A. (2021). Computational Text Professionalization using Neural Sequence-to-Sequence Models.
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Bäumer, F. S., Kersting, J., Buff, B., &; Geierhos, M. (2020). Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P 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 
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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.
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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.
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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.
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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.
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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 
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Kersting, J., &; Geierhos, M. (2020). What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (pp. 263--272). Setúbal, Portugal: SCITEPRESS.
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Karl, H., Kundisch, D., Meyer auf der Heide, F., &; Wehrheim, H. (2020). A Case for a New IT Ecosystem: On-The-Fly Computing. Business &; Information Systems Engineering, 62(6), 467–481.https://doi.org/10.1007/s12599-019-00627-x 
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Chen, W.-F., Al-Khatib, K., Wachsmuth, H., &; Stein, B. (2020). Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity. Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 149–154.
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Syed, S., Chen, W.-F., Hagen, M., Stein, B., Wachsmuth, H., &; Potthast, M. (2020). Task Proposal: Abstractive Snippet Generation for Web Pages. Proceedings of the 13th International Conference on Natural Language Generation (INLG 2020), 237–241.
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Chen, W.-F., Al-Khatib, K., Stein, B., &; Wachsmuth, H. (2020). Detecting Media Bias in News Articles using Gaussian Bias Distributions. Findings of the Association for Computational Linguistics: EMNLP 2020, 4290–4300.
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Chen, W.-F., Syed, S., Stein, B., Hagen, M., &; Potthast, M. (2020). Abstractive Snippet Generation. Proceedings of the Web Conference 2020, 1309–1319.
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Alshomary, M., Syed, S., Potthast, M., &; Wachsmuth, H. (2020). Target Inference in Argument Conclusion Generation. Proceedings of 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), 4334–4345.
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Bäumer, F. S., &; Geierhos, M. (2019). Requirements Engineering in OTF-Computing. In encyclopedia.pub. Basel, Switzerland: MDPI.
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Bäumer, F. S., Kersting, J., &; Geierhos, M. (2019). Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches. Computers, 8(1).https://doi.org/10.3390/computers8010022 
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Khaluf, L. (2019). Organic Programming of Dynamic Real-Time Applications. Universität Paderborn.
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Friesen, E. (2019). Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn.
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Chen, W.-F., Al-Khatib, K., Hagen, M., Wachsmuth, H., &; Stein, B. (2019). Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition. Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom, 76–82.
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Bäumer, F. S., &; Geierhos, M. (2018). How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, &; F. Meziane (Eds.), Proceedings of the 23rd International Conference on Natural Language and Information Systems (Vol. 10859, pp. 509–513). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-91947-8_53 
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Kim, Y., Lee, S., Dollmann, M., &; Geierhos, M. (2018). Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure. International Journal of Advanced Science and Technology, 112, 123–136.https://doi.org/10.14257/ijast.2018.112.12 
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DOI: 10.14257/ijast.2018.112.12

Bäumer, F. S., &; Geierhos, M. (2018). NLP in OTF Computing: Current Approaches and Open Challenges. In R. Damasevidius &; G. Vasiljevien (Eds.), Proceedings of the 24th International Conference on Information and Software Technologies (ICIST 2018) (Vol. 920, pp. 559–570). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-99972-2_46 
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DOI: 10.1007/978-3-319-99972-2_46

Bäumer, F. S., &; Geierhos, M. (2018). Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-based Configuration of Text Analysis Pipelines. In Proceedings of the 51st Hawaii International Conference on System Sciences (pp. 5746–5755). Big Island, Waikoloa Village.https://doi.org/10125/50609 
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Geierhos, M. (2018). Unschärfe bei der Interpretation natürlichsprachlicher Anforderungsbeschreibungen. In S. Freitag, M. Geierhos, R. Asmani, &; J. I. Haug (Eds.), Unschärfe - Der Umgang mit fehlender Eindeutigkeit (1st ed., pp. 111–128). Paderborn, Germany: Ferdinand Schöningh.
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Bäumer, F. S., &; Geierhos, M. (2018). How to Deal with Inaccurate Service Requirements? Insights in Our Current Approach and New Ideas. In K. Schmid, P. Spoletini, E. Ben Charrada, Y. Chisik, F. Dalpiaz, A. Ferrari,  A. Zamansky (Eds.), Joint Proceedings of REFSQ-2018 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track co-located with the 23rd International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2018) (Vol. 2075). Utrecht, The Netherlands: CEUR-WS.org.
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Friesen, E., Bäumer, F. S., &; Geierhos, M. (2018). CORDULA: Software Requirements Extraction Utilizing Chatbot as Communication Interface. In K. Schmid, P. Spoletini, E. Ben Charrada, Y. Chisik, F. Dalpiaz, A. Ferrari,  A. Zamansky (Eds.), Joint Proceedings of REFSQ-2018 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track co-located with the 23rd International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2018) (Vol. 2075). Utrecht, The Netherlands: CEUR-WS.org.
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Caron, M., Bäumer, F. S., &; Geierhos, M. (2018). Back to Basics: Extracting Software Requirements with a Syntactic Approach. In K. Schmid, P. Spoletini, E. Ben Charrada, Y. Chisik, F. Dalpiaz, A. Ferrari,  A. Zamansky (Eds.), Joint Proceedings of REFSQ-2018 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track co-located with the 23rd International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2018) (Vol. 2075). Utrecht, The Netherlands: CEUR-WS.org.
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Chen, W.-F., Wachsmuth, H., Al Khatib, K., &; Stein, B. (2018). Learning to Flip the Bias of News Headlines. Proceedings of the 11th International Conference on Natural Language Generation, 79–88.
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Chen, W.-F., Hagen, M., Stein, B., &; Potthast, M. (2018). A User Study on Snippet Generation: Text Reuse vs. Paraphrases. Proceedings of the 41st International ACM SIGIR Conference on Research &; Development in Information Retrieval, 1033–1036.
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Potthast, M., Chen, W.-F., Hagen, M., &; Stein, B. (2018). A Plan for Ancillary Copyright: Original Snippets. Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval, 3–5.
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Geierhos, M., &; Bäumer, F. S. (2017). Guesswork? Resolving Vagueness in User-Generated Software Requirements. In H. Christiansen, M. D. Jiménez-López, R. Loukanova, &; L. S. Moss (Eds.), Partiality and Underspecification in Information, Languages, and Knowledge (1st ed., pp. 65–108). Newcastle upon Tyne, UK: Cambridge Scholars Publishing.
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Bäumer, F. S., Dollmann, M., &; Geierhos, M. (2017). Studying Software Descriptions in SourceForge and App Stores for a better Understanding of real-life Requirements. In F. Sarro, E. Shihab, M. Nagappan, M. C. Platenius, &; D. Kaimann (Eds.), Proceedings of the 2nd ACM SIGSOFT International Workshop on App Market Analytics (pp. 19–25). New York, NY, USA: ACM.https://doi.org/10.1145/3121264.3121269 
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Grobbel, F. (2017). Was kommt zuerst? Erkennung von zeitlichen Abläufen infunktionalen Softwareanforderungsbeschreibungen. Universität Paderborn.
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Theda, M. (2017). Was ist gemeint? Strukturell ambige Sätze als Herausforderung für Parsing-Ansätze. Universität Paderborn.
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Platenius, M. C., Arifulina, S., &; Schäfer, W. (2017). MatchBox: A Framework for Dynamic Configuration of Service Matching Processes (Extended Abstract). In Tagungsband Software Engineering (pp. 81--82).
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Bäumer, F. S. (2017). Indikatorbasierte Erkennung und Kompensation von ungenauen und unvollständig beschriebenen Softwareanforderungen. Universität Paderborn.https://doi.org/10.17619/UNIPB/1-157 
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van Rooijen, L., Bäumer, F. S., Platenius, M. C., Geierhos, M., Hamann, H., &; Engels, G. (2017). From User Demand to Software Service: Using Machine Learning to Automate the Requirements Specification Process. In 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW) (pp. 379–385). Piscataway, NJ, USA: IEEE.https://doi.org/10.1109/REW.2017.26 
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Schwichtenberg, S., Gerth, C., &; Engels, G. (2017). From Open API to Semantic Specifications and Code Adapters. In Proceedings of the 24th IEEE International Conference on Web Services (ICWS) (pp. 484--491).
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Krammer, I. (2017). Denn wir wissen, was gemeint ist: Erweiterung bestehender Lösungen zur lexikalischen Disambiguierung durch einen kontextsensitiven Whitelist-Ansatz. Universität München.
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Kim, Y.-S., Lee, S.-W., Dollmann, M., &; Geierhos, M. (2017). Semantic Annotation of Software Requirements with Language Frame. International Journal of Software Engineering for Smart Device, 4(2), 1–6.
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Wever, M. D. (2017). Active Learning of User Requirement Specifications in Dynamic Software Service Markets. Universität Paderborn.
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Wever, M. D., van Rooijen, L., &; Hamann, H. (2017). Active Coevolutionary Learning of Requirements Specifications from Examples. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) (pp. 1327--1334).https://doi.org/10.1145/3071178.3071258 
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Sergio Djoum Temdjim, A. (2017). Evaluation of Software Reputation Matching Based on App Reviews. Universität Paderborn.
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Rehmer, L. (2017). Erweiterung eines kontextsensitiven Autovervollständigungstools zur natürlichsprachlichen Softwarespezifikation. Universität Paderborn.
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Platenius, M. C. (2016). Fuzzy Matching of Comprehensive Service Specifications. Universität Paderborn.
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Dollmann, M. (2016). Frag die Anwender: Extraktion und Klassifikation von funktionalen Softwareanforderungen aus User-Generated-Content. Universität Paderborn.
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Heck, E. (2016). Ontologie-Erstellung mittels Text-Mining aus App-Marktplätzen am Beispiel des Google Marketplace. Universität Paderborn.
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Schwentker, C. (2016). Ontologie-basierte Extraktion funktionaler Softwareanforderungen am Fallbeispiel mobiler Kommunikationsapplikationen. Universität Paderborn.
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Dollmann, M., &; Geierhos, M. (2016). On- and Off-Topic Classification and Semantic Annotation of User-Generated Software Requirements. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 1807–1816). Austin, TX, USA: Association for Computational Linguistics (ACL).
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Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., &; Schäfer, W. (2016). Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, (8), 739–759.https://doi.org/10.1109/TSE.2016.2632115 
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Geierhos, M., &; Bäumer, F. S. (2016). How to Complete Customer Requirements: Using Concept Expansion for Requirement Refinement. In E. Métais, F. Meziane, M. Saraee, V. Sugumaran, &; S. Vadera (Eds.), Proceedings of the 21st International Conference on Applications of Natural Language to Information Systems (NLDB) (Vol. 9612, pp. 37–47). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-41754-7_4 
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Reckhorn, L. (2016). Herausforderungen im Umgang mit unvollständigen Softwareanforderungen durch Semantic Role Labeling. Universität Paderborn.
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Stanco, S. (2016). Modellierung von domänenspezifischen Ontologien im Anwendungsfall funktionaler Softwareanforderungen. Universität Paderborn.
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Platenius, M. C., Josifovska, K., van Rooijen, L., Arifulina, S., Becker, M., Engels, G., &; Schäfer, W. (2016). An Overview of Service Specification Language and Matching in On-The-Fly Computing (.3). Universität Paderborn.
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Schwichtenberg, S. (2016). Automatized Derivation of Comprehensive Specifications for Black-box Services. In Proceedings of the 38th International Conference on Software Engineering Companion (ICSE) (pp. 815–818).https://doi.org/10.1145/2889160.2889271 
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Kühne, T., Hamann, H., Arifulina, S., &; Engels, G. (2016). Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application. In Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016) (pp. 278--293).https://doi.org/10.1007/978-3-319-30668-1_18 
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Bäumer, F. S., &; Geierhos, M. (2016). Running out of Words: How Similar User Stories Can Help to Elaborate Individual Natural Language Requirement Descriptions. In G. Dregvaite &; R. Damasevicius (Eds.), Proceedings of the 22nd International Conference on Information and Software Technologies (ICIST) (Vol. 639, pp. 549–558). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-46254-7_44 
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Arifulina, S. (2016). Solving Heterogeneity for a Successful Service Market. Universität Paderborn.https://doi.org/10.17619/UNIPB/1-13 
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van Rooijen, L., &; Hamann, H. (2016). Requirements Specification-by-Example Using a Multi-Objective Evolutionary Algorithm. In Proceedings of 24th IEEE International Requirements Engineering Conference (RE 2016) (pp. 3--9).https://doi.org/10.1109/REW.2016.015 
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Vollmers, D. (2016). Vergleich von Disambiguierungsansätzen bei Anforderungsbeschreibungen. Universität Paderborn.
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Arifulina, S., Platenius, M. C., Mohr, F., Engels, G., &; Schäfer, W. (2015). Market-Specific Service Compositions: Specification and Matching. In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet (pp. 333--340).https://doi.org/10.1109/SERVICES.2015.58 
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Börding, P. (2015). Fuzzy Matching von Vor- und Nachbedingungen in Servicespezikationen. Universität Paderborn.
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Geierhos, M., Bäumer, F. S., Schulze, S., &; Stuß, V. (2015). Filtering Reviews by Random Individual Error. In M. Ali, Y. S. Kwon, C.-H. Lee, J. Kim, &; Y. Kim (Eds.), Proceedings of the 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2015) (Vol. 9101, pp. 305–315). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-19066-2_30 
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Neumann, C. (2015). Ein Framework für Fuzzy Service Matching basierend auf Fuzzy Sets. Universität Paderborn.
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Bruns, M. (2015). Design of an Evaluation Strategy for Fuzzy Service Matching. Universität Paderborn.
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Börding, P., Bruns, M., &; Platenius, M. C. (2015). Comprehensive Service Matching with MatchBox. In 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE’15) (pp. 974--977).https://doi.org/10.1145/2786805.2803181 
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Huma, Z. (2015). Automatic Service Discovery and Composition for heterogeneous service partners. Universität Paderborn.
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Platenius, M. C., Arifulina, S., &; Schäfer, W. (2015). MatchBox: A Framework for Dynamic Configuration of Service Matching Processes. In Proceedings of the 18th International ACM Sigsoft Symposium on Component-Based Software Engineering (CBSE’15) (pp. 75–84).https://doi.org/10.1145/2737166.2737174 
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Geierhos, M., Schulze, S., &; Bäumer, F. S. (2015). What did you mean? Facing the Challenges of User-generated Software Requirements. In S. Loiseau, J. Filipe, B. Duval, &; J. van den Herik (Eds.), Proceedings of the 7th International Conference on Agents and Artificial Intelligence (ICAART), Special Session on Partiality, Underspecification, and Natural Language Processing (PUaNLP 2015) (pp. 277–283). Setúbal, Portugal: SciTePress - Science and Technology Publications.https://doi.org/10.5220/0005346002770283 
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Brangewitz, S., Jungmann, A., Petrlic, R., &; Platenius, M. C. (2014). Towards a Flexible and Privacy-Preserving Reputation System for Markets of Composed Services. In Proceedings of the 6th International Conferences on Advanced Service Computing (SERVICE COMPUTATION) (pp. 49–57).
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Arifulina, S., Becker, M., Platenius, M. C., &; Walther, S. (2014). SeSAME: Modeling and Analyzing High-Quality Service Compositions. In Proceedings of the 29th IEEE/ACM International Conference on Automated Software Engineering (ASE 2014) (pp. 839–842).https://doi.org/10.1145/2642937.2648621 
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Petrlic, R., Jungmann, A., Platenius, M. C., Schäfer, W., &; Sorge, C. (2014). Security and Privacy Challenges in On-The-Fly Computing. In Tagungsband der 4. Konferenz Software-Technologien und -Prozesse (STeP 2014) (pp. 131–142).
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von Detten, M., Platenius, M. C., &; Becker, S. (2014). Reengineering Component-Based Software Systems with Archimetrix. Journal of Software and Systems Modeling, (4), 1239--1268.https://doi.org/10.1007/s10270-013-0341-9 
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Gao, Y. (2014). Combination of Service Matching Steps in Consideration of Efficiency and Fuzziness. Universität Paderborn.
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Becker, M., Platenius, M. C., &; Becker, S. (2014). Cloud Computing Reduces Uncertainties in Quality-of-Service Matching! In Proceedings of the 2nd International Workshop on Cloud Service Brokerage (CSB) (pp. 153–159).https://doi.org/10.1007/978-3-319-14886-1_15 
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Bano, D. (2014). Modeling and Matching of Reputation of Services in On-The-Fly Computing. Universität Paderborn.
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Bunse, M. (2014). Measuring Transformation-induced Uncertainty in Service Matching: A Feasibility Study. Universität Paderborn.
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Platenius, M. C., Arifulina, S., Petrlic, R., &; Schäfer, W. (2014). Matching of Incomplete Service Specifications Exemplified by Privacy Policy Matching. In Proceedings of the 4th International Workshop on Adaptive Services for the Future Internet (pp. 6–17).https://doi.org/10.1007/978-3-319-14886-1_2 
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Arifulina, S., Platenius, M. C., Gerth, C., Becker, S., Engels, G., &; Schäfer, W. (2014). Market-optimized Service Specification and Matching. In X. Franch, A. Ghose, G. Lewis, &; S. Bhiri (Eds.), Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC 2014) (pp. 543–550).https://doi.org/10.1007/978-3-662-45391-9_47 
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