A method of SMS spam filtering based on AdaBoost algorithm

Xipeng Zhang, Gang Xiong*, Yuexiang Hu, Fenghua Zhu, Xisong Dong, Timo R. Nyberg

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)


Short message is one of the most common communication media for mobile subscribers, so major mobile operators are devoted to improve their Short Message Service (SMS). However, the annoying and undesired messages, also named message spam or simply spam, not only worsen the users' experience, but also cause their complaints on SMS. In this paper, we present a novel Chinese SMS spam filtering framework based on AdaBoost algorithm to provide accurate and effective short messages classification. Three content-based weak filters are introduced to boost the performance of final classification decision. Results from Receiver Operating Characteristics (ROC) analysis prove the proposed method has such advantages as higher efficiency and fewer parameters over those established SMS spam filtering methods. The application of the proposed method is expected to block the most spam for mobile subscribers and improve the service quality of SMS. With simple data processing and few training parameters, the proposed method can be applied into the practice of short text classification.

Original languageEnglish
Title of host publicationProceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016
Number of pages5
ISBN (Electronic)9781467384148
Publication statusPublished - 27 Sep 2016
MoE publication typeA4 Article in a conference publication
EventWorld Congress on Intelligent Control and Automation - Guilin, China
Duration: 12 Jun 201615 Jun 2016
Conference number: 12


ConferenceWorld Congress on Intelligent Control and Automation
Abbreviated titleWCICA


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