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  • About eBiltegia  
    • What is eBiltegia? 
    •   About eBiltegia
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    •   Mondragon Unibertsitatea's Institutional Policy on Open Access to scientific documents and teaching materials
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    •   eBiltegia Digital Preservation Guidelines
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Short Messages Spam Filtering Combining Personality Recognition and Sentiment Analysis 

Ezpeleta, Enaitz; Garitano, Iñaki; Zurutuza, Urko (World Scientific Publishing, 2017)
Currently, short communication channels are growing up due to the huge increase in the number of smartphones and online social networks users. This growth attracts malicious campaigns, such as spam campaigns, that are a ...
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Short Messages Spam Filtering Using Sentiment Analysis 

Ezpeleta, Enaitz; Zurutuza, Urko (Springer International Publishing, 2016)
In the same way that short instant messages are more and more used, spam and non-legitimate campaigns through this type of communication systems are growing up. Those campaigns, besides being an illegal online activity, ...
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Nuevos Paradigmas de Análisis Basados en Contenidos para la Detección del Spam en RRSS 

Ezpeleta, Enaitz (Sociedad Española para el Procesamiento del Lenguaje Natural, 2018)
Tesis doctoral realizada por Enaitz Ezpeleta Gallastegi en Mondragon Unibertsitatea, dentro del grupo de Sistemas Inteligentes para Sistemas Industriales, dirigida por los Doctores Urko Zurutuza Ortega (Mondragon Unibertsitatea) ...
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New approaches for content-based analysis towards online social network spam detection 

Ezpeleta, Enaitz (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2016)
Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. Although spam filtering techniques are capable of detecting significant percentage of the spam messages, the problem is ...
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Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data 

Cernuda, Carlos; Ezpeleta, Enaitz; Alberdi Aramendi, Ane (IOS Press, 2020)
Background: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated. Objective: The objective of the study was to validate predictive models to separately ...
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A study of the personalization of spam content using Facebook public information 

Ezpeleta, Enaitz; Zurutuza, Urko (Oxford University Press, 2017)
Millions of users per day are affected by unsolicited email campaigns. Spam filters are capable of detecting and avoiding an increasing number of messages, but researchers have quantified a response rate of a 0.006% [1], ...
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A Mood Analysis on Youtube Comments and a Method for Improved Social Spam Detection 

Ezpeleta, Enaitz; Iturbe, Mikel; Garitano, Iñaki; Velez de Mendizabal, Iñaki; Zurutuza, Urko (Springer, 2018)
In the same manner that Online Social Networks (OSN) usage increases, non-legitimate campaigns over these types of web services are growing. This is the reason why signi cant number of users are affected by social spam ...
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SDRS: A new lossless dimensionality reduction for text corpora 

Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (Elsevier Ltd., 2020)
In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, ...
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Multi-objective evolutionary optimization for dimensionality reduction of texts represented by synsets 

Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (PeerJ, 2023)
Despite new developments in machine learning classification techniques, improving the accuracy of spam filtering is a difficult task due to linguistic phenomena that limit its effectiveness. In particular, we highlight ...
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poliSPAM: Analisis de la eficiencia del spam personalizado utilizando informacion publica de redes sociales 

Ezpeleta, Enaitz; Uribeetxeberria, Roberto; Zurutuza, Urko; Arenaza-Nuño, Ignacio (Mondragon Unibertsitatea, 2012)
Las campañas de envío de correos electrónicos no deseados siguen siendo una de las mayores amenazas que afectan a millones de usuarios al día. Si bien los filtros antispam son capaces de detectar y rechazar un número elevado ...
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AuthorEzpeleta, Enaitz (11)Zurutuza, Urko (8)Velez de Mendizabal, Iñaki (4)Garitano, Iñaki (2)Alberdi Aramendi, Ane (1)Arenaza-Nuño, Ignacio (1)Cernuda, Carlos (1)Iturbe, Mikel (1)Uribeetxeberria, Roberto (1)Subjectspam (6)polarity (4)security (4)sentiment analysis (4)online social networks (3)Multi-objective evolutionary algorithms (2)Semantic-based feature reduction (2)SMS (2)Spam filtering (2)Synset-based representation (2)... View MoreDate Issued2020 - 2023 (4)2012 - 2019 (7)Has File(s)Yes (11)

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