Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2020; 21st International C Cesar Analide,Paulo Novais,Hujun Yin Conference proc

针叶树

A Novel Evaluation Metric for Synthetic Data Generationlly) personally identifiable information as inputs (.) and existing SDG algorithms PrivBayes and DPGroupFields to generate synthetic data (.) based on them. We then test our evaluation metric for different values of privacy budget .. Based on our experiments we conclude that the proposed composite e

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的阐明

An Intelligent Procedure for the Methodology of Energy Consumption in Industrial Environmentsrnet of Things (IoT) and Data Analytics provide the intelligence needed to optimally operate these complex industrial environments. The work presented in this manuscript contributes to the definition of the aforementioned intelligent data-driven approaches, defining a systematic, intelligent procedu

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Intelligent Data Engineering and Automated Learning – IDEAL 2020978-3-030-62365-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Video Semantics Quality Assessment Using Deep Learningtic information extracted from videos and the information obtained from text news of the same event. Deep learning techniques are used to detect objects in the video scenes. News articles are represented by a set of relevant terms automatically extracted from the news. This paper describes our method and an evaluation of it.

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高兴一回

A Preprocessing Approach for Class-Imbalanced Data Using SMOTE and Belief Function Theoryation performance. Specifically, SMOTE is a popular oversampling technique which modifies the training data by adding artificial minority samples. However, SMOTE may create instances in noisy and overlapping areas, far from safe regions. To tackle this issue, we propose SMOTE-BFT, in which we use th