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The problem of data stream classification is challenging because of many practical aspects associated with efficient processing and temporal behavior of the stream. Two such well studied aspects are infinite length and concept-drift. Since a data stream may be considered a continuous process, which is theoretically infinite in length, it is impractical to store and use all the historical data for...
This proposal presents the integration of interpolating global cubic splines into a general function regression framework to approximate curved functions or more dimensional curves based on noisy observations. We rearrange the iterative process of spline parameter calculation and obtain a practical linear matrix formulation. Then we employ Bayesian techniques to estimate spline model parameters and...
Vehicles will exchange much information in the future in order to efficiently maintain their inner model of the environment. Before they can belief received pieces of information, they must evaluate their reliability. Trust is a mechanism to estimate this reliability based on the sender. As cars often drive the same route, they meet each other again and again. They can establish friendship-like relations...
Data quality is a critical problem in modern databases. Data entry forms present the first and arguably best opportunity for detecting and mitigating errors, but there has been little research into automatic methods for improving data quality at entry time. In this paper, we propose USHER, an end-to-end system for form design, entry, and data quality assurance. Using previous form submissions, USHER...
Collected data often contains uncertainties. Probabilistic databases have been proposed to manage uncertain data. To combine data from multiple autonomous probabilistic databases, an integration of probabilistic data has to be performed. Until now, however, data integration approaches have focused on the integration of certain source data (relational or XML). There is no work on the integration of...
We present a semi-supervised learning (SSL) method for building domain-specific language models (LMs) from general-domain data using probabilistic latent semantic analysis (PLSA). The proposed technique first performs topic decomposition (TD) on the combined dataset of domain-specific and general-domain data. Then it derives latent topic distribution of the interested domain, and derives domain-specific...
Testing is one of the most widely used techniques to increase the quality and reliability of complex software systems. In this paper we extend our previous work on passive testing with invariants to incorporate (probabilistic) knowledge obtained from users of the system under test. In order to apply our technique, we need to obtain a set of invariants compiling the relevant properties of the system...
Results of fMRI studies show that on tasks involving reasoning about probabilities, brain activation patterns differ between those who make judgments based on ratio rules and those who make judgments based on intuitive heuristics. These results suggest a three-layer adaptive resonance theory model connecting the amygdala and three executive prefrontal regions (orbital, anterior cingulate, and dorsolateral)...
Underwater sensor networks have the potential to enhance our ability of observing and monitoring underwater physical phenomena, warning against natural disasters, and protecting critical areas, such as ports, from malicious attacks. However, the adverse underwater conditions and the limits of underwater acoustic communication, such as volatile link quality and temporal node isolation, remarkably affect...
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