@inproceedings{4392198c6162437fb8e4d55f52583c36,
title = "Highly discriminative features for phishing email classification by SVD",
abstract = "Unstructured text documents have drawn recently more attention, because with growing amount of text documents, there is a need to classify them automatically. But an important problem in field of text categorization is the huge dimensional and very sparse dataset which hurts generalization performance of classifiers. This paper presents a Singular Value Decomposition (SVD) technique to email classification, in order to compress optimally only the kind of documents (in our experiments email classes) and to retain the most informative and discriminate features from an email document. The performance evaluation is performed on email dataset which is publicly available to demonstrate the benefit of the LSA.",
keywords = "Data mining, Dimension reduction, Email classification, Feature Extraction",
author = "Masoumeh Zareapoor and Pourya Shamsolmoali and \{Afshar Alam\}, M.",
note = "Publisher Copyright: {\textcopyright} Springer India 2015.; 2nd International Conference on Information Systems Design and Intelligent Applications, INDIA 2015 ; Conference date: 08-01-2015 Through 09-01-2015",
year = "2015",
doi = "10.1007/978-81-322-2250-7\_65",
language = "英语",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "649--656",
editor = "Sanyal, \{Manas Kumar\} and Anirban Mukhopadhyay and J.K. Mandal and Satapathy, \{Suresh Chandra\} and Sarkar, \{Partha Pratim\}",
booktitle = "Information Systems Design and Intelligent Applications - Proceedings of 2nd International Conference, INDIA 2015",
address = "德国",
}