Titlebook: Advances in Artificial Intelligence – IBERAMIA 2022; 17th Ibero-American Ana Cristina Bicharra Garcia,Mariza Ferro,Julio Ce Conference pro

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https://doi.org/10.1007/978-3-476-05613-9onger feelings from the readers than simple facts, sentiment analysis has been widely used to detect fake news. Nevertheless, sarcasm, irony, and even jokes use similar written styles, making the distinction between fake and fact harder to catch automatically. We propose a new fake news Classifier t

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https://doi.org/10.1007/978-3-476-05613-9s’ efficiency is a trade-off of accuracy, time to solution, and energy consumption. This leads to a multi-objective optimization problem implemented through the Genetic Algorithms (GA). We present the GA scheme and operators designed for this work focused on the architecture and hyperparameter optim

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https://doi.org/10.1007/978-3-476-00123-8 absence of information about the dynamics in these node representations can harm the accuracy and increase processing time of machine learning tasks related to these applications. We propose a biased random walk method named Evolving Node Embedding (.), which leverages the sequential relationship o

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https://doi.org/10.1007/978-3-476-04577-5e., it uses the entire training data set for prediction, makes it unsuitable for most current big data applications. Several strategies, such as tree-based or hashing-based estimators, have been proposed to improve the efficiency of the kernel density estimation method. The novel density kernel dens

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