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In online shopping, most of consumers will not clear their return reasons when submitting return requests (e.g., select the option “other reasons”). Prior literature mostly investigates into the return event at the transaction level, and the underlying force of returns remains untracked. To deal with this problem, we propose a machine learning algorithm named as trust-aware random walk model (TARW)...
Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome‐sequencing...
Distributed Denial of Service (DDoS) attacks grow rapidly and become one of the fatal threats to the Internet. Automatically detecting DDoS attack packets is one of the main defense mechanisms. Conventional solutions monitor network traffic and identify attack activities from legitimate network traffic based on statistical divergence. Machine learning is another method to improve identifying performance...
Fraud detection in electricity consumption is a major challenge for power distribution companies. While many pattern recognition techniques have been applied to identify electricity theft, they often require extensive handcrafted feature engineering. Instead, through deep layers of transformation, nonlinearity, and abstraction, Deep Learning (DL) automatically extracts key features from data. In this...
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