Titlebook: Natural Language Processing and Information Systems; 27th International C Paolo Rosso,Valerio Basile,Farid Meziane Conference proceedings 2

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Marcelo Fischer,Rejwanul Haque,Paul Stynes,Pramod Pathaklysis, probabilistic neural networks and multi-layer feed-forward neural networks. In addition, the book describes local and global optimization methods and their application to seismic reflection data. Given i978-3-030-45664-1978-3-030-45662-7Series ISSN 2364-9119 Series E-ISSN 2364-9127

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Natural Language Processing and Information Systems27th International C

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On-Device Language Detection and?Classification of?Extreme Short Text from?Calendar Titles Across La. Our language detection models with accuracies of 96%, outperform existing language detection tools by?20% and our event classifiers achieved 92%, 94%, 87% and 90% accuracies across, English, Korean and German, French respectively. Currently tested CEC module architecture delivers the fastest (4?ms

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Identifying Fake News in?Brazilian Portuguese This paper investigates the application of BERT for fake news identification in Brazilian Portuguese. In addition to BERT, we also tested a number of widely-used machine learning (ML) algorithms, methods and strategies for this task. We found that fake news identification models built using advance

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e limited in scope, offers a laboratory analysis of the attenuation effects for sur- face layers. The authors confirm that seismic attenuation in sedimentary la978-3-7643-6263-8978-3-0348-8415-0Series ISSN 2504-3625 Series E-ISSN 2504-3633

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Convolutional Graph Neural Networks for?Hate Speech Detection in?Data-Poor Settingson that considers the similarity among nodes in the graph to improve the final classification. Particularly, our goal is to overcome hate speech detection in data-poor settings. As a result we found that our model is more stable than other state-of-the-art deep learning models with few data in the considered datasets.

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