TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Y1 - 2020 U6 - http://dx.doi.org/10.1145/3387940.3391478 SP - 603 EP - 610 ER - TY - CHAP A1 - Siebigteroth, Ines A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - A Study on Improving Corpus Creation by Pair Annotation T2 - Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019) Y1 - 2019 SN - 1613-0073 SP - 40 EP - 44 ER - TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Cost-efficient quality assurance of natural language processing tools through continuous monitoring with continuous integration T2 - 3rd International Workshop on Software Engineering Research and Industrial Practice Y1 - 2016 U6 - http://dx.doi.org/10.1145/2897022.2897029 N1 - SER&IP’16, May 17 2016, Austin, TX, USA SP - 46 EP - 52 ER - TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Bilof, Randall T1 - Metrics driven research collaboration: focusing on common project goals continuously T2 - Proceedings : 2017 IEEE/ACM 4th International Workshop on Software Engineering Research and Industrial Practice : SER&IP 2017 : 21 May 2017 Buenos Aires, Argentina Y1 - 2017 SN - 978-1-5386-2797-6 U6 - http://dx.doi.org/10.1109/SER-IP.2017..6 SP - 41 EP - 47 PB - IEEE Press CY - Piscataway, NJ ER - TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - NLP Lean Programming Framework: Developing NLP Applications More Effectively T2 - Proceedings of NAACL-HLT 2018: Demonstrations, New Orleans, Louisiana, June 2 - 4, 2018 N2 - This paper presents NLP Lean Programming framework (NLPf), a new framework for creating custom natural language processing (NLP) models and pipelines by utilizing common software development build systems. This approach allows developers to train and integrate domain-specific NLP pipelines into their applications seamlessly. Additionally, NLPf provides an annotation tool which improves the annotation process significantly by providing a well-designed GUI and sophisticated way of using input devices. Due to NLPf’s properties developers and domain experts are able to build domain-specific NLP applications more efficiently. NLPf is Opensource software and available at https:// gitlab.com/schrieveslaach/NLPf. Y1 - 2018 U6 - http://dx.doi.org/10.18653/v1/N18-5001  ER - TY - CHAP A1 - Schreiber, Marc A1 - Hirtbach, Stefan A1 - Kraft, Bodo A1 - Steinmetzler, Andreas ED - Kowalewski, Stefan T1 - Software in the city: visual guidance through large scale software projects T2 - Software Engineering 2013 : Fachtagung des GI-Fachbereichs Softwaretechnik, 26. Februar-1. März 2013 in Aachen. (GI-Edition ; 213) Y1 - 2013 SN - 978-3-88579-607-7 ; 978-3-88579-609-1 SP - 213 EP - 224 PB - Ges. für Informatik CY - Bonn ER - TY - CHAP A1 - Schreiber, Marc A1 - Barkschat, Kai A1 - Kraft, Bodo T1 - Using Continuous Integration to organize and monitor the annotation process of domain specific corpora T2 - 5th International Conference on Information and Communication Systems (ICICS) : 1-3 April 2014, Irbid, Jordanien Y1 - 2014 SN - 978-1-4799-3022-7 U6 - http://dx.doi.org/10.1109/IACS.2014.6841958 SP - 1 EP - 6 ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Winkens, Marvin A1 - Zündorf, Albert T1 - Catalog integration of low-quality product data by attribute label ranking T2 - Proceedings of the 9th International Conference on Data Science, Technology and Applications - Volume 1: DATA Y1 - 2020 SN - 978-989-758-440-4 U6 - http://dx.doi.org/10.5220/0009831000900101 SP - 90 EP - 101 ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Winkens, Marvin A1 - Zündorf, Albert T1 - Catalog integration of heterogeneous and volatile product data T2 - DATA 2020: Data Management Technologies and Applications N2 - The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations. Y1 - 2021 SN - 978-3-030-83013-7 U6 - http://dx.doi.org/10.1007/978-3-030-83014-4_7 N1 - International Conference on Data Management Technologies and Applications, DATA 2020, 7-9 July SP - 134 EP - 153 PB - Springer CY - Cham ER - TY - CHAP A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Siebigteroth, Ines A1 - Zündorf, Albert T1 - Schema Matching with Frequent Changes on Semi-Structured Input Files: A Machine Learning Approach on Biological Product Data T2 - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS Y1 - 2019 SN - 978-989-758-372-8 U6 - http://dx.doi.org/10.5220/0007723602080215 SP - 208 EP - 215 ER -