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 ...
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...
متن کاملTowards SMS Spam Filtering: Results under a New Dataset
The growth of mobile phone users has lead to a dramatic increasing of SMS spam messages. Recent reports clearly indicate that the volume of mobile phone spam is dramatically increasing year by year. In practice, fighting such plague 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...
متن کاملText normalization and semantic indexing to enhance Instant Messaging and SMS spam filtering
The rapid popularization of smartphones has contributed to the growth of online Instant Messaging and SMS usage as an alternative way of communication. The increasing number of users, along with the trust they inherently have in their devices, makes such messages a propitious environment for spammers. In fact, reports clearly indicate that volume of spam over Instant Messaging and SMS is dramat...
متن کاملSpam Filtering Using Statistical Data Compression Models
Spam filtering poses a special problem in text categorization, of which the defining characteristic is that filters face an active adversary, which constantly attempts to evade filtering. Since spam evolves continuously and most practical applications are based on online user feedback, the task calls for fast, incremental and robust learning algorithms. In this paper, we investigate a novel app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2012
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2012.02.053