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StaResGRU-CNN with CMedLMs: a stacked residual GRU-CNN with pre-trained biomedical language models for predictive intelligence
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Machine Learning approaches for Topic and Sentiment Analysis in multilingual opinions and low-resource languages: From English to Guarani
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Brazilian Portuguese verbal databases ; Bases lexicais verbais do português brasileiro
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In: Domínios de Lingu@gem; Ahead of Print ; 1980-5799 (2022)
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Representation learning of natural language and its application to language understanding and generation
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Detecting weak and strong Islamophobic hate speech on social media
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An Empirical Study of Factors Affecting Language-Independent Models
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Using Geolocated Text to Quantify Location in Real Estate Appraisal
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TSM: Measuring the Enticement of Honeyfiles with Natural Language Processing
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Modeling Phishing Decision using Instance Based Learning and Natural Language Processing
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Abstract:
Phishing is the practice of deceiving humans into disclosing sensitive information or inappropriately granting access to a secure system. Unfortunately, there is a severe lack of theoretical models to adequately explain and predict the cognitive dynamics underlying end-user susceptibility to phishing emails. This paper reports findings from an Instance-Based Learning (IBL) model developed to predict human response to emails obtained from a laboratory experiment. Particularly, this work investigates the effectiveness of using established natural language processing methods, such as LSA, GloVe, and BERT, to represent email text within IBL models. We found that using representations that consider contextual meanings assigned by humans could enable IBL agents to predict human response with high accuracy (>80%). In addition, we found that traditional NLP methods that capture semantic meanings in natural language may not be effective at representing how people may encode and recall email messages. We discuss the implications of these findings.
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Keyword:
cognitive modeling; Cyber Deception and Cyberpsychology for Defense; deception; natural language processing; phishing
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URL: https://doi.org/10.24251/HICSS.2022.276 http://hdl.handle.net/10125/79609
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What to prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development
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Eine agentenbasierte Architektur für Programmierung mit gesprochener Sprache
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Um método adaptativo para análise sintática do Português Brasileiro. ; An adaptive method for syntactic analysis of Brazilian Portuguese.
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Padovani, Djalma. - : Biblioteca Digital de Teses e Dissertações da USP, 2022. : Universidade de São Paulo, 2022. : Escola Politécnica, 2022
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Multitask Pointer Network for Multi-Representational Parsing
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