| Συγγραφείς: | Kanaris I., Kanaris K., Stamatatos E. |
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| Τίτλος: | Spam Detection Using Character N-grams |
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| Συνέδριο: | 4th Hellenic Conference on AI (SETN 2006): Advances in Artificial Intelligence |
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| Editors: | G. Antoniou, G. Potamias, C. Spyropoulos, D. Plexousakis |
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| Ed: | Όχι |
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| Eds: | Ναι |
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| Σελίδες: | 95–104 |
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| Να εμφανιστεί: | Όχι |
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| Μήνας: | |
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| Έτος: | 2006 |
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| Τόπος: | |
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| Εκδότης: | |
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| Δεσμός: | |
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| Όνομα αρχείου: | |
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| Περίληψη: | This paper presents a content-based approach to spam detection
based on low-level information. Instead of the traditional 'bag of words' representation,
we use a 'bag of character n-grams' representation which avoids the
sparse data problem that arises in n-grams on the word-level. Moreover, it is
language-independent and does not require any lemmatizer or 'deep' text preprocessing.
Based on experiments on Ling-Spam corpus we evaluate the proposed
representation in combination with support vector machines. Both binary
and term-frequency representations achieve high precision rates while maintaining
recall on equally high level, which is a crucial factor for anti-spam filters, a
cost sensitive application. |
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English