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We introduce a new distance measure that is better suited than traditional methods at detecting similarities in patient records by referring to a concept hierarchy.The new distance measure improves on distance measures for categorical values by taking the path distance between concepts in a hierarchy into account. We evaluate and compare the new measure on a data set of 836 patients.The new measure...
In this paper we present several content-based recommendation methods for a QA system that rely and use extensively the structure of a domain-specific taxonomy. Our goal is to add semantics to a typical content-based RS in order to improve the quality of the recommendations by mapping relevant keywords from the existing taxonomy to the available questions. In order to test and evaluate the effectiveness...
Modal parameter identification plays an important role within damage identification strategies in the field of structural health monitoring. The identification of natural frequencies and damping ratios by means of dynamic measurements provides a good information basis for further analysis. In this paper we review the Dynamic Data System (DDS) approach using autoregressive (AR) models in order to overcome...
In this paper we present an architecture for integrating IT-Service-Management-data and a method for relationship identification using a domain-specific taxonomy. This knowledge can be used for semantic data integration by automatically accessing different data sources and identifying dependencies between various IT-Service-items. This can be done by using existing categories and documents to build...
The foundations and technologies of Case-Based Reasoning (CBR) has emerged from academic projects to commercial used applications which are supporting everyday life. Everything changes in the long term which includes planning, modeling and developing reasoning software due to new aspects such as big data and various new services provided by cloud computing. Maintaining a balance between achieving...
In the past years research done in the field of structural health monitoring has been focusing on the development of a robust and cost-effective monitoring solution by integrating and extending technologies from various engineering and information technology disciplines. There are many data mining, statistical computing and graphics tools available that can be successfully applied and integrated into...
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