Titlebook: Ontology Alignment; Bridging the Semanti Marc Ehrig Book 2007 Springer-Verlag US 2007 Bridging.Data Integration.Gap.Information Systems.Int

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Iatrogenic

tions, and it was shown to have an effective performance in practical application. We are currently studying the association technique of home service (by using data mining) that can happen when IPD predicts home service by the home service predictor.

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own parallel models. Such characterisations give a method to translate parallel algorithms to optical algorithms and facilitate the application of the complexity theory toolbox to optical computers. In the present work we improve on these results. Specifically we tighten a lower bound and present so

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tors the user action, and performs learning based on this feedback. Moreover, the system has characteristics of offering more personalized content as well as reducing the response time due to reuse of the content generated by same group category. A prototype was implemented in order to evaluate the

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Scenariosresented in the beginning. For this reason, the next sections will examine concrete use cases and derive requirements for ontology alignment from them. As they make clear in which direction the research needs to head, these requirements are another important part of the foundations. Based on these f

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