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Mining actuarial risk predictors in accident descriptions using recurrent neural networks
Baillargeon, Jean-Thomas; Lamontagne, Luc; Marceau, Etienne - In: Risks 9 (2021) 1, pp. 1-14
One crucial task of actuaries is to structure data so that observed events are explained by their inherent risk factors. They are proficient at generalizing important elements to obtain useful forecasts. Although this expertise is beneficial when paired with conventional statistical models, it...
Persistent link: https://www.econbiz.de/10013200677
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Real-time wireless acquisition of process data
Zhang, Ye - 2011
This study discusses a novel method called automatic process measurement, which is based on the idea of mining process data from workflow logs. We improve the process mining technique by using Bluetooth wireless technology to do real-time acquisition of process data. The automatic measurement...
Persistent link: https://www.econbiz.de/10010333095
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Analyse sensorischer E-Commerce-Elemente mittels Big-Data-Methoden und Künstlicher Intelligenz: Automatisierung sensorischer Bewertungen von E-Commerce- und Social-Media-Plattforme...
Hamacher, Kevin; Blach, Maike; Kozlik, Jan; Muster, Felix; … - 2023
Kundinnen und Kunden kommunizieren, kaufen und teilen Produkte und Dienstleistungen über digitale Plattformen, in denen technische Möglichkeiten zur Präsentation sensorischer Elemente im Normalfall auf visuelle, akustische und schriftliche Elemente begrenzt sind. Um das sensorische...
Persistent link: https://www.econbiz.de/10014377033
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Stock picking via nonsymmetrically pruned binary decision trees
Andriyashin, Anton - 2008
Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of the...
Persistent link: https://www.econbiz.de/10010263732
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Testing the significance of calendar effects
Hansen, Peter Reinhard; Lunde, Asger - 2003
When evaluating the significance of calendar effects, such as those associated with Monday and January, it is necessary to control for all possible calendar effects to avoid spurious results. The downside of having to control for a large number of possible calendar effects is that it diminish...
Persistent link: https://www.econbiz.de/10010318856
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IT-Integration in Zeiten von Digitalisierung – (k)ein alter Hut?
Huber, Melanie; Rentrop, Christopher; Zimmermann, Stephan - In: HMD Praxis der Wirtschaftsinformatik 58 (2020) 2, pp. 425-443
Unternehmensarchitektur von Unternehmen über die Jahre stetig erhöht. Das Aufkommen nutzerfreundlicher Informationstechnologie (IT … Unternehmensarchitektur. Darüber hinaus treibt dieser IT-Einsatz die Digitalisierung in den Unternehmen maßgeblich voran. Dies wirft die Frage … Unternehmensarchitektur. Er beleuchtet, dass eine gemeinsame Sprache die Basis für IT-Integrationsprojekte ist und dass eine Kultur, in der …
Persistent link: https://www.econbiz.de/10014504215
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Workshop on Service Monitoring, Adaptation and Beyond: A workshop held at the ServiceWave 2008 conference - Proceedings
Karastoyanova, Dimka (contributor);  … - 2009
This ICB Research Report constitutes the proceedings of the first workshop on Monitoring, Adaptation and Beyond (MONA+ 2008), which was held on December 13, 2008 in Madrid, Spain. MONA+ has been collocated with the ServiceWave 2008 conference.
Persistent link: https://www.econbiz.de/10010308874
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Insurance: an R-Program to Model Insurance Data
Marin-Galiano, Marcos; Christmann, Andreas - 2004
Data sets from car insurance companies often have a high-dimensional complex dependency structure. The use of classical statistical methods such as generalized linear models or Tweedie?s compound Poisson model can yield problems in this case. Christmann (2004) proposed a general approach to...
Persistent link: https://www.econbiz.de/10010296633
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Robust Learning from Bites for Data Mining
Christmann, Andreas; Steinwart, Ingo; Hubert, Mia - 2006
Some methods from statistical machine learning and from robust statistics have two drawbacks. Firstly, they are computer-intensive such that they can hardly be used for massive data sets, say with millions of data points. Secondly, robust and non-parametric confidence intervals for the...
Persistent link: https://www.econbiz.de/10010296722
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Data Mining Projekte im unternehmerischen Umfeld : eine empirische Studie deutscher Unternehmen
Hilbert, Andreas - 2002
In dieser Studie werden zunächst die konzeptionellen Grundlagen des Customer Relationship Managements und der sog. CRM-Systeme dargestellt sowie die Einbettung von Data Warehouse und Data Mining Technologie in diesem Kontext erörtert. Danach erfolgt eine Literatur gestützte Diskussion...
Persistent link: https://www.econbiz.de/10010296833