منابع مشابه
Email Spam Detection Using Customized SimHash Function
E-mail communication is a narrative challenging in present days, because a problem can be done in that communication from one to other emails process generation. The problem is spam mail combination in original mail interaction. This is the major task for sending information from one to other persons, if it important to that particular person. So to solve these problems effectively traditionall...
متن کاملEmail classification for Spam Detection using Word Stemming
Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...
متن کاملEmail classification for Spam Detection using Word Stemming
Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...
متن کاملEmail classification for Spam Detection using Word Stemming
Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...
متن کاملSymbiotic filtering for spam email detection
This paper presents a novel spam filtering technique called Symbiotic Filtering (SF) that aggregates distinct local filters from several users to improve the overall performance of spam detection. SF is an hybrid approach combining some features from both Collaborative (CF) and Content-Based Filtering (CBF). It allows for the use of social networks to personalize and tailor the set of filters t...
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ژورنال
عنوان ژورنال: Information Technology and Nanotechnology
سال: 2019
ISSN: 1613-0073
DOI: 10.18287/1613-0073-2019-2416-165-172