Dr. rer. nat.

Rüping, Stefan

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  • Publication
    Integration and reuse of data mining in business processes - A pattern-based approach
    ( 2011)
    Wegener, Dennis orcid-logo
    ;
    Rüping, Stefan
    Today's business applications demand high flexibility in processing information and extracting knowledge from data. Thus, data mining becomes more and more an integral part of operating a business. However, the integration of data mining into business processes still requires a lot of coordination and manual adjustment. This paper aims at reducing this effort by reusing successful data mining solutions. We describe a novel approach to facilitating the integration based on process patterns for data mining and demonstrate that these patterns allow for easy reuse and can significantly speed up the process of integration. We empirically evaluate our approach in a case study of fraud detection in the healthcare domain.
  • Publication
    Towards an environment for data mining based analysis processes in bioinformatics & personalized medicine
    ( 2011)
    Wegener, Dennis orcid-logo
    ;
    Rossi, Simona
    ;
    Buffa, Francesca
    ;
    Delorenzi, Mauro
    ;
    Rüping, Stefan
    Bioinformatics and data mining procedures are collaborating to implement and evaluate tools and procedures for prediction of disease recurrence and progression, response to treatment, as well as new insights into various oncogenic pathways [1], [2], [3], [4] by taking into account the user needs and their heterogeneity. Based on these advances, medicine is undergoing a revolution that is even transforming the nature of health care from reactive to proactive [5]. The p-medicine (www.p-medicine.eu) consortium is creating a biomedical platform to facilitate the translation from current practice to a predictive, personalized, preventive, participatory and psycho-cognitive medicine by integrating VPH models, clinical practice, imaging and genomics data. In this paper, we present the challenges for data mining based analysis in bio- and medical informatics and our approach towards a data mining environment addressing these requirements in the p-medicine platform.