The paper aims to present a Spam Detection system by a Content Analysis based on Machine Leaning. The system is composed of six units: Tokenization and Cleaning words, Lemmatization, Stopping Word Removal and Synonym Replacement, Term Selection, Bag-of-Words Representer, and Classifier. Experiments performed on two different datasets, i.e., SpamAssassin and Trec2007 show satisfactory results, comparable with the state of the art.
Spam Detection by Machine Learning-Based Content Analysis
Camastra F.
;Ciaramella A.;Staiano A.
2020-01-01
Abstract
The paper aims to present a Spam Detection system by a Content Analysis based on Machine Leaning. The system is composed of six units: Tokenization and Cleaning words, Lemmatization, Stopping Word Removal and Synonym Replacement, Term Selection, Bag-of-Words Representer, and Classifier. Experiments performed on two different datasets, i.e., SpamAssassin and Trec2007 show satisfactory results, comparable with the state of the art.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
