@inbook{83673440c14b4ee8a32ae613a9a2668c,
title = "A Non-genuine Message Detection Method Based on Unstructured Datasets",
abstract = "The identification of non-genuine or malicious messages poses a variety of challenges due to the continuous changes in the techniques utilised by cyber-criminals. In this article, we discuss a further evaluation of the text spam recognition method introduced in [1], which is based on semantic properties of documents to assess the level of maliciousness. Further experimental results show the accuracy and potential of our approach.",
keywords = "Spam detection, big data, data mining, text mining",
author = "Marcello Trovati and Richard Hill and Nik Bessis",
year = "2015",
doi = "10.1109/3PGCIC.2015.108",
language = "English",
isbn = "9781467394734",
series = "Proceedings - 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "597--600",
booktitle = "Proceedings - 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2015",
address = "United States",
}