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Titlebook: Mashups; Concepts, Models and Florian Daniel,Maristella Matera Textbook 2014 Springer-Verlag Berlin Heidelberg 2014 Application Integration

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Florian Daniel,Maristella Materasz as either positive or negative. This problem has received attention in both machine learning as well as formal methods communities, and it has been shown to have exponential worst-case complexity in the general case as well as for many restrictions. In this paper, we focus on learning . Boolean f
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Florian Daniel,Maristella Materaergy consumption or cost. But this is typically with respect to the . value of these quantities, which can mask important aspects of the full probability distribution, such as the possibility of high-risk, low-probability events or multimodalities. We propose a . extension of probabilistic model che
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Introduction, tools for “data mashups.” Yet, when it comes to a concrete discussion of the topic, it is not uncommon to discover at some point that the involved parties in the discussion actually have very different interpretations of what mashups are and what they are not. Typical discussion points are whether
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Data and Application Integrationargely investigated in software engineering and data management. A huge body of methods have been proposed in the areas more affected by the integration problem, such as enterprise information integration, enterprise application integration, and service composition. The core problems underlying thes
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