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Pervasive applications rely on data captured from the physical world through sensor devices. Data provided by these devices, however, tend to be unreliable. The data must, therefore, be cleaned before an application can make use of them, leading to additional complexity for application development and deployment. Here we present Extensible Sensor stream Processing (ESP), a framework for building sensor...
We propose a novel algorithm, QuIET, for binary classification of texts. The method automatically generates a set of span queries from a set of annotated documents and uses the query set to categorize unlabeled texts. QuIET generates models that are human understandable. We describe the method and evaluate it empirically against Support Vector Machines, demonstrating a comparable performance for a...
Sensor devices produce data that are unreliable, low-level, and seldom able to be used directly by applications. In this paper, we propose metaphysical data independence (MDI), a layer of independence that shields applications from the challenges that arise when interacting directly with sensor devices. The key philosophy behind MDI is that applications do not deal with any aspect of physical device...
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