Research on Naive Bayesian Spam SMS Filtering Based on MapReduce
نویسندگان
چکیده
منابع مشابه
SMS 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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Bayesian spam filtering is a classification method based on the theory of probability and statistics, and the Bayesian spam filtering based on Mapreduce can solve the defect of the traditional Bayesian spam filtering that consumes large amounts of system resources and network resources when the mail set is pre-training. It needs to classify mails manually in the pre-training phase of mail set, ...
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It has recently been argued that a Naive Bayesian classifier can be used to filter unsolicited bulk e-mail (“spam”). We conduct a thorough evaluation of this proposal on a corpus that we make publicly available, contributing towards standard benchmarks. At the same time we investigate the effect of attribute-set size, training-corpus size, lemmatization, and stop-lists on the filter’s performan...
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Bayesian filtering is one of the most famous anti-spam measures. However, there is no standard implementation for treatment of Japanese emails by Bayesian filtering. In this paper, we compare several conceivable ways to treat Japanese emails about tokenizing and corpus separation. In addition, we give experimental results and some knowledge obtained by the experiments.
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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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ژورنال
عنوان ژورنال: Computer Science and Application
سال: 2016
ISSN: 2161-8801,2161-881X
DOI: 10.12677/csa.2016.67054