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Titlebook: Database and Expert Systems Applications; 33rd International C Christine Strauss,Alfredo Cuzzocrea,Ismail Khalil Conference proceedings 202

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Comparison of Sequence Variants and the Application in Electronic Medical Records of sequence variants is an important problem in practical applications. To conduct comparisons, it is necessary to detect the common and uncommon parts of sequence variants, but a suitable method is not available. In this study, we developed a method for comparing sequence variants by providing app
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Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networksle in many domains such as credit card fraud identification, network intrusion detection, medical image processing and so on. The inherent class imbalance in datasets is one of the major reasons why this problem is difficult to solve. The small number of outliers are not adequate to characterize the
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https://doi.org/10.1007/978-3-642-86003-4manner. In addition, Alps achieves the outstanding performance of distributed stream processing system with the least overhead. Compared with state-of-the-art scaling approach DS2, Alps reduces the end-to-end latency by 2 orders of magnitude on high-speed skewed stream and avoids the waste of resources on low-speed or balanced stream.
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https://doi.org/10.1007/978-1-4614-4388-9ing the prediction bias caused by mis-click. The proposed model is experimented on MovieLens, Amazon video game and Amazon digital music datasets, and the results show that our model achieves the best performance in all datasets.
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https://doi.org/10.1007/978-94-009-2522-9 model on the NTU RGB-D datasets, and the experimental results demonstrate the superiority of our model against other baseline methods in terms of recognition effectiveness in understanding mutual actions.
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