While process mining has gained much attention in the past decade, surprisingly, discovering structural errors (i.e., deadlock and lack of synchronization) from event logs has seldom been studied. Since event logs may...
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Recommender systems aim to filter information effectively and recommend useful sources to match users' requirements. However, the exponential growth of information in recent social networks may cause low predictio...
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Nowadays, video surveillance is widespread used to achieve security life in the construction of smart city. As a result, prevalence of video surveillance equipments and technologies enables pedestrian identification a...
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Internet of Things (IoT) based industrial defect detection has attracted more and more attention. As a key component of intelligent manufacturing, defect detection is very important. Although deep learning (DL) can re...
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Weak light environment poses challenges for target detection. It is difficult for the existing target detection algorithms to track the target in the noise-flooded image. In order to improve the accuracy of the target...
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The surging development of Artificial Intelligence-Generated Content (AIGC) marks a transformative era of the content creation and production. Edge servers promise attractive benefits, e.g., reduced service delay and ...
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The problem of constrained subset selection from a large data stream for profit maximization has many applications in web data mining and machine learning, such as social advertising, team formation and recommendation...
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Motivation is a key factor in improving the enthusiasm and work performance of crowdsourcing workers. It is important for crowdsourcing platforms to allocate tasks. In order to increase the enthusiasm of workers and t...
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Few-shot learning (FSL) learns to recognize objects based on very limited examples of each category. An intuitive approach for FSL is to generate additional samples for few-shot categories. This is typically achieved ...
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The collaborative filtering-based recommender algorithm suffers the interaction sparsity problem and cold start problem, experts have introduced knowledge graphs (KGs) and applied graph neural network models to achiev...
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