Titlebook: Web Engineering; 20th International C Maria Bielikova,Tommi Mikkonen,Cesare Pautasso Conference proceedings 2020 Springer Nature Switzerlan

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Who’s Behind That Website? Classifying Websites by the Degree of Commercial Intentsupervised machine learning algorithms. Based on a large real-world data set, we evaluate our model with respect to its effectiveness and efficiency and observe the best performance with a multilayer perceptron.

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Conference proceedings 2020e organized in topical sections named:..User interface technologies; performance of Web technologies; machine learning; testing of Web applications; emotion detection; location-aware applications; sentiment analysis; open data; liquid Web applications; Web-based learning; PhD symposium; demos and posters..

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0302-9743 cations; emotion detection; location-aware applications; sentiment analysis; open data; liquid Web applications; Web-based learning; PhD symposium; demos and posters..978-3-030-50577-6978-3-030-50578-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Improving Detection Accuracy for?Malicious JavaScript Using GAN This paper proposes an efficient method for improving the classifiers’ recognition rate in detecting malicious JavaScript based on Generative Adversarial Networks (GAN). The output from the GAN is used to train classifiers. Experimental results show that our method can achieve better accuracy with a limited set of labeled sample.

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: Providing Scalable and Reliable Messaging Service in Distributed Systemsctice. Experiments are conducted in a real system, and the results show that NuMessage can achieve superior performance when there are message consuming failures happening. Moreover, we have adopted NuMessage in eBay for some time to process 12 billion of messages per day.