Institute of Information Systems
Organisational unit: Institute
- Junior professorship for Information Systems, in particular Data Analytics
- Professorship for Computer Engineering
- Professorship for Information Systems, in particular Artificial Intelligence and Explainability
- Professorship for Information Systems, in particular Data Science
- Professorship for Information Systems, in particular Digital Transformation and Information Management
- Professorship for Information Systems, in particular E-Business and Knowledge Management
- Professorship for Information Systems, in particular Machine Learning
- Professorship for Information Systems, in particular Network Science
Organisation profile
At the Institute of Information Systems (IIS) of the Leuphana University we work on innovative topics in Information Systems and Data Science. The main focus is on digital transformation, e-health, e-commerce, business analytics, sports and e-learning. Methodologically, we focus on the development and use of machine learning and artificial intelligence methods for the modeling and solution of data-driven decision problems. Additional quantitative (e.g. graphs, optimization) and qualitative (e.g. interviews, reference modeling) methods complement this spectrum. Cooperating with other universities, companies, and institutions of the civil society plays an important role in our work.
Main research areas
At the Institute of Information Systems there are currently 6 professors and numerous research assistants. Our main research areas include digital transformation, e-health, e-commerce, business analytics, sports, and e-learning. Details can be found on the websites of the work groups and in the central research database of Leuphana. The Institute of Information Systems organized a number of events and conferences at Leuphana (e.g. ITEE 2013, final round of the German National Computer Science Competition 2014, MKWI 2018).
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Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses
Xie, L., Li, H. & Luttmann, L., 01.06.2023, In: European Journal of Operational Research . 307, 2, p. 713-730 18 p.Research output: Journal contributions › Journal articles › Research › peer-review
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Foreword to applied data science, demo, and nectar tracks
Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F., 01.01.2019, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F. (eds.). Cham: Springer Verlag, Vol. 3. p. V-VI 2 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11053).Research output: Contributions to collected editions/works › Other › Research
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‘Forewarned is Forearmed’: Overcoming Multifaceted Challenges of Digital Innovation Units
Raabe, J.-P., Horlach, B., Schirmer, I. & Drews, P., 2020, 26th Americas Conference on Information Systems, AMCIS 2020: Strategic and competitive uses of IT. A. F. I. S. (ed.). Atlanta: AIS eLibrary, 10 p. (Proceedings of the Americas Conference on Information Systems (AMCIS); vol. 2020).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Finding the Best Match — a Case Study on the (Text‑) Feature and Model Choice in Digital Mental Health Interventions
Zantvoort, K., Scharfenberger, J., Boß, L., Lehr, D. & Funk, B., 12.2023, In: Journal of Healthcare Informatics Research. 7, 4, p. 447-479 33 p., 00148.Research output: Journal contributions › Journal articles › Research › peer-review
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Finanzmathematische Effektivzins-Berechnungsmethoden
Kober, J., Knöll, H.-D. & Rometsch, U., 1992, Mannheim: BI Wissenschaftsverlag. 206 p.Research output: Books and anthologies › Monographs › Transfer
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Finanzanalyse und Finanzrating
Weinrich, G. & Jacobs, J., 01.01.2007, Finanzrating: Gestaltungsmöglichkeiten zur Verbesserung der Bonität. Achleitner, A.-K. (ed.). Wiesbaden: Dr. Gabler Verlag, p. 15-53 39 p.Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research
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Fehler beim Controlling
Weinrich, G., 1988, In: Harvard Business Manager. 3, p. 119-123 5 p.Research output: Journal contributions › Journal articles › Research
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Feature selection for density level-sets
Kloft, M., Nakajima, S. & Brefeld, U., 2009, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Buntine, W., Grobelnik, M., Mladenic, D. & Shawe-Taylor, J. (eds.). Heidelberg: Springer Verlag, p. 692-704 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 5781 LNAI, no. PART 1).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Feature Extraction and Aggregation for Predicting the Euro 2016
Tavakol, M., Zafartavanaelmi, H. & Brefeld, U., 09.2016, In: CEUR Workshop Proceedings. 1842, 1842, 7 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
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FaST: A linear time stack trace alignment heuristic for crash report deduplication
Rodrigues, I. M., Aloise, D. & Fernandes, E. R., 17.10.2022, The 2022 Mining Software Repositories Conference: MSR 2022, Proceedings; 18-20 May 2022, Virtual; 23-24 May 2022, Pittsburgh, Pennsylvania. New York: Institute of Electrical and Electronics Engineers Inc., p. 549-560 12 p. (Proceedings - IEEE/ACM International Conference on Mining Software Repositories ).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review