The Impact of Feature Extraction and Selection on SMS Spam Filtering
نویسندگان
چکیده
منابع مشابه
SMS spam filtering: Methods and data
Mobile or SMS spam is a real and growing problem primarily due to the availability of very cheap bulk pre-pay SMS packages and the fact that SMS engenders higher response rates as it is a trusted and personal service. SMS spam filtering is a relatively new task which inherits many issues and solutions from email spam filtering. However it poses its own specific challenges. This paper motivates ...
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The Impact of Feature Selection on Signature-Driven Spam Detection
Signature-driven spam detection provides an alternative to machine learning approaches and can be very effective when near-duplicates of essentially the same message are sent in high volume [20]. Unfortunately, signatures can also be brittle to small alterations of message content. In this work we propose a technique for increasing signature robustness, targeting the I-Match algorithm [6], but ...
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Search engine is one of the most important tools for managing the massive amount of distributed web content. Web spamming tries to deceive search engines to rank some pages higher than they deserve. Many methods have been proposed to combat web spamming and to detect spam pages. One basic one is using classification, i.e., learning a classification model for classifying web pages to spam or non...
متن کاملSMS Spam Filtering Technique Based on Artificial Immune System
The Short Message Service (SMS) have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Naïve Bayesian algorithm is one of the most effective approaches used in filtering te...
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ژورنال
عنوان ژورنال: Electronics and Electrical Engineering
سال: 2013
ISSN: 2029-5731,1392-1215
DOI: 10.5755/j01.eee.19.5.1829