Sciweavers

Share
DOCENG
2011
ACM

Contributions to the study of SMS spam filtering: new collection and results

8 years 7 months ago
Contributions to the study of SMS spam filtering: new collection and results
The growth of mobile phone users has lead to a dramatic increasing of SMS spam messages. In practice, fighting mobile phone spam is difficult by several factors, including the lower rate of SMS that has allowed many users and service providers to ignore the issue, and the limited availability of mobile phone spam-filtering software. On the other hand, in academic settings, a major handicap is the scarcity of public SMS spam datasets, that are sorely needed for validation and comparison of different classifiers. Moreover, as SMS messages are fairly short, content-based spam filters may have their performance degraded. In this paper, we offer a new real, public and non-encoded SMS spam collection that is the largest one as far as we know. Moreover, we compare the performance achieved by several established machine learning methods. The results indicate that Support Vector Machine outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further com...
Tiago A. Almeida, José María G&oacut
Added 18 Dec 2011
Updated 18 Dec 2011
Type Journal
Year 2011
Where DOCENG
Authors Tiago A. Almeida, José María Gómez Hidalgo, Akebo Yamakami
Comments (0)
books