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Detecting DGA domains with recurrent neural networks and side information

This work devise a notion of difficulty for DGA families called the smashword score, which accurately reflects how much a DGA family's domains look like they are made from natural English words, and describes the new modeling approach, which is a combination of a novel recurrent neural network architecture with domain registration side information.
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Smartphone Security: An overview of emerging threats.

The mobile threat landscape has undergone rapid growth as smartphones have increased in popularity, and the landscape continues to evolve with mobile bitcoin miners, botnets, and ransomware.
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Alejandro Mosquera at SemEval-2021 Task 1: Exploring Sentence and Word Features for Lexical Complexity Prediction

The conclusion is that a combination of lexical, contextual and semantic features can still produce strong baselines when compared against human judgement.
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The Use of Metrics for Measuring Informality Levels in Web 2.0 Texts

This paper demonstrates that the discovery of informality levels in Web 2.0 texts can be improved by incorporating formality and informality scores by using unsupervised machine learning techniques.
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Tratamiento de textos para mejorar la comprensión lectora en alumnos con deficiencias auditivas

La metodologia aplicada para resolver los distintos problemas relacionados with el objetivo a conseguir, the hipotesis of trabajo and las tareas and los objetivos parciales alcanzados are described.
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Towards Facilitating the Accessibility of Web 2 . 0 Texts through Text Normalisation

The experimental results show that TENOR is an adequate tool for this task, facilitating text simplification with current NLP tools when required and also making Web 2.0 texts more accessible to people unfamiliar with these text types.

On Detecting Messaging Abuse in Short Text Messages using Linguistic and Behavioral patterns

This paper analyzes the effectiveness of machine learning filters based on linguistic and behavioral patterns in order to detect short text spam and abusive users in the network and explores different ways to deal with short text message challenges such as tokenization and entity detection by using text normalization and substring clustering techniques.
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DLSI-Volvam at RepLab 2013: Polarity Classification on Twitter Data

This paper describes the participants' participation in the proling (po- larity classication) task of the RepLab 2013 workshop, and covers three dierent approaches that combine machine learning and lexicon-based techniques with an emotional concept model.
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TENOR: A Lexical Normalisation Tool for Spanish Web 2.0 Texts

This study proposes the normalisation of non-normative lexical variants in Spanish Web 2.0 texts by restoring the canonical version of Twitter texts and increasing the F1 measure of a state-of-the-art approach for English texts by a 10%.
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The Study of Informality as a Framework for Evaluating the Normalisation of Web 2.0 Texts

This study proposes a text normalisation evaluation framework using informality levels and its application to Web 2.0 texts, and hypothesizes that the analysis of Informality levels can be used to evaluate text normalization techniques.
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