Nektaria Potha

We show that the profile-based paradigm (where all samples by one author are treated cumulatively) can be very effective surpassing the performance of PAN-2013 winners without using any information from external sources. Expand

We propose a modification of the Impostors method that focuses on both appropriate selection of imposter documents and enhanced comparison of impostor documents with the documents under investigation. Expand

In this paper, we propose the use of an intrinsic profile-based verification method that is based on latent semantic indexing (LSI). Expand

Cyber bullying is a new phenomenon resulting from the advance of new communication technologies including the Internet, cell phones and Personal Digital Assistants. Expand

We propose a simple stacking ensemble as well as a dynamic ensemble selection approach that can use the most reliable base models for each verification case separately. Expand

The openness of the Android operating system and its immense penetration into the market makes it a hot target for malware writers. Expand

The present article deals with sexual cyberbullying, a serious subject that has gained significant attention throughout recent years of emerging social media platforms. Expand

We deal with the cyberbullying issue as a time series modelling methodology, aiming at the recognition of bullying patterns within the questions posed by a predator to his victims. Expand

In this paper, we propose two algorithms, one instance-based and one profile-based (all known documents are treated cumulatively) that are able to outperform state-of the-art methods in several benchmark datasets. Expand

We examine several author verification methods that cover the main paradigms and demonstrate that LDA is better combined with extrinsic methods, while the most effective intrinsic method is based on LSI. Expand