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Artificial Neural Network for Websites Classification with Phishing Characteristics
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作者 Ricardo Pinto Ferreira andréa martiniano +4 位作者 Domingos Napolitano Marcio Romero Dacyr Dante De Oliveira Gatto Edquel Bueno Prado Farias Renato José Sassi 《Social Networking》 2018年第2期97-109,共13页
Several threats are propagated by malicious websites largely classified as phishing. Its function is important information for users with the purpose of criminal practice. In summary, phishing is a technique used on t... Several threats are propagated by malicious websites largely classified as phishing. Its function is important information for users with the purpose of criminal practice. In summary, phishing is a technique used on the Internet by criminals for online fraud. The Artificial Neural Networks (ANN) are computational models inspired by the structure of the brain and aim to simu-late human behavior, such as learning, association, generalization and ab-straction when subjected to training. In this paper, an ANN Multilayer Per-ceptron (MLP) type was applied for websites classification with phishing cha-racteristics. The results obtained encourage the application of an ANN-MLP in the classification of websites with phishing characteristics. 展开更多
关键词 Artificial INTELLIGENCE Artificial Neural Network Pattern Recognition PHISHING CHARACTERISTICS SOCIAL Engineering
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“If We Only Knew How You Feel”—A Comparative Study of Automated vs. Manual Classification of Opinions of Customers on Digital Media
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作者 Huoston Rodrigues Batista José Carmino Gomes Junior +3 位作者 Marcelo Drudi Miranda andréa martiniano Renato José Sassi Marcos Antonio Gaspar 《Social Networking》 2019年第1期74-83,共10页
The Web development has drastically changed the human interaction and communication, leading to an exponential growth of data generated by users in various digital media. This mass of data provides opportunities for u... The Web development has drastically changed the human interaction and communication, leading to an exponential growth of data generated by users in various digital media. This mass of data provides opportunities for understanding people’s opinions about products, services, processes, events, political movements, and organizational strategies. In this context, it becomes important for companies to be able to assess customer satisfaction about their products or services. One of the ways to evaluate customer sentiment is the use of Sentiment Analysis, also known as Opinion Mining. This research aims to compare the efficiency of an automatic classifier based on dictionary with the classification by human jurors in a set of comments made by customers in Portuguese language. The data consist of opinions of service users of one of the largest Brazilian online employment agencies. The performance evaluation of the classification models was done using Kappa index and a Confusion Matrix. As the main finding, it is noteworthy that the agreement between the classifier and the human jurors came to moderate, with better performance for the dictionary-based classifier. This result was considered satisfactory, considering that the Sentiment Analysis in Portuguese language is a complex task and demands more research and development. 展开更多
关键词 SENTIMENT Analysis OPINION Mining Social Media
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