TY - CHAP A1 - Schreiber, Marc A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Metrics Driven Research Collaboration: Focusing on Common Project Goals Continuously T2 - 39th International Conference on Software Engineering, May 20-28, 2017 - Buenos Aires, Argentina N2 - Research collaborations provide opportunities for both practitioners and researchers: practitioners need solutions for difficult business challenges and researchers are looking for hard problems to solve and publish. Nevertheless, research collaborations carry the risk that practitioners focus on quick solutions too much and that researchers tackle theoretical problems, resulting in products which do not fulfill the project requirements. In this paper we introduce an approach extending the ideas of agile and lean software development. It helps practitioners and researchers keep track of their common research collaboration goal: a scientifically enriched software product which fulfills the needs of the practitioner’s business model. This approach gives first-class status to application-oriented metrics that measure progress and success of a research collaboration continuously. Those metrics are derived from the collaboration requirements and help to focus on a commonly defined goal. An appropriate tool set evaluates and visualizes those metrics with minimal effort, and all participants will be pushed to focus on their tasks with appropriate effort. Thus project status, challenges and progress are transparent to all research collaboration members at any time. Y1 - 2017 N1 - Software Engineering in Practice (SEIP). ICSE2017 Vorabversion der Autoren 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 - GEN A1 - Nobisrath, Ulrich A1 - Zündorf, Albert A1 - George, Tobias A1 - Ruben, Jubeh A1 - Kraft, Bodo T1 - Software Stories Guide N2 - Software Stories are a simple graphical notation for requirements analysis and design in agile software projects. Software Stories are based on example scenarios. Example scenarios facilitate the communication between lay people or domain experts and software experts. Y1 - 2017 ER - TY - CHAP A1 - Schmidts, Oliver A1 - Boltes, Maik A1 - Kraft, Bodo A1 - Schreiber, Marc T1 - Multi-pedestrian tracking by moving Bluetooth-LE beacons and stationary receivers T2 - 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 18-21 September 2017, Sapporo, Japan Y1 - 2017 N1 - International Conference on Indoor Positioning and Indoor Navigation <8, 2017, Sapporo, Japan> SP - 1 EP - 4 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 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Schreiber, Marc A1 - Zündorf, Albert T1 - Continuously evaluated research projects in collaborative decoupled environments T2 - 2018 ACM/IEEE 5th International Workshop on Software Engineering Research and Industrial PracticePractice, May 29, 2018, Gothenburg, Sweden : SER&IP' 18 N2 - Often, research results from collaboration projects are not transferred into productive environments even though approaches are proven to work in demonstration prototypes. These demonstration prototypes are usually too fragile and error-prone to be transferred easily into productive environments. A lot of additional work is required. Inspired by the idea of an incremental delivery process, we introduce an architecture pattern, which combines the approach of Metrics Driven Research Collaboration with microservices for the ease of integration. It enables keeping track of project goals over the course of the collaboration while every party may focus on their expert skills: researchers may focus on complex algorithms, practitioners may focus on their business goals. Through the simplified integration (intermediate) research results can be introduced into a productive environment which enables getting an early user feedback and allows for the early evaluation of different approaches. The practitioners’ business model benefits throughout the full project duration. Y1 - 2018 SP - 1 EP - 9 PB - ACM CY - New York, NY 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 - 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 - 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 - Klöser, Lars A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert T1 - Multi-attribute relation extraction (MARE): simplifying the application of relation extraction T2 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications - DeLTA N2 - Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations. Y1 - 2021 SN - 978-989-758-526-5 U6 - http://dx.doi.org/10.5220/0010559201480156 N1 - Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, DeLTA2021, July 7-9, 2021 SP - 148 EP - 156 ER -