Titlebook: Web Information Systems and Applications; 15th International C Xiaofeng Meng,Ruixuan Li,Gansen Zhao Conference proceedings 2018 Springer Na

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书目名称Web Information Systems and Applications影响因子(影响力)




书目名称Web Information Systems and Applications影响因子(影响力)学科排名




书目名称Web Information Systems and Applications网络公开度




书目名称Web Information Systems and Applications网络公开度学科排名




书目名称Web Information Systems and Applications被引频次




书目名称Web Information Systems and Applications被引频次学科排名




书目名称Web Information Systems and Applications年度引用




书目名称Web Information Systems and Applications年度引用学科排名




书目名称Web Information Systems and Applications读者反馈




书目名称Web Information Systems and Applications读者反馈学科排名

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Deceit

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Osteoarthritis

Liang Li,Zhongmin Zhang,Shengli Wue theorems and should be able to follow a substantial portion of the mathematical development. The entire book can be read by someone familiar with the basic as978-1-4419-2804-7978-1-4757-6097-2Series ISSN 0066-5452 Series E-ISSN 2196-968X

somnambulism

A Frequent Sequential Pattern Based Approach for Discovering Event Correlationsions in an IoT environment, and proposes an algorithm to discover event correlations. We transform the event correlation discovery problem into a time-constrained frequent sequence mining problem. Moreover, we apply our approach in anomaly warning in a coal power plant. We have made extensive experiments to verify the effectiveness of our approach.

Mucosa

A Frequent Sequential Pattern Based Approach for Discovering Event Correlationsions in an IoT environment, and proposes an algorithm to discover event correlations. We transform the event correlation discovery problem into a time-constrained frequent sequence mining problem. Moreover, we apply our approach in anomaly warning in a coal power plant. We have made extensive experiments to verify the effectiveness of our approach.

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Multilingual Short Text Classification via Convolutional Neural Network in multilingual text semantics, we introduce convolutional neural network into the model, and output classification prediction results. This model can process multilingual textual data well. Experiments show that convolutional neural network combined with auto-associative memory improves classifica