Exploration of Neuro-Fuzzy Spam Filtering based on Naive Bayes Filters

نویسندگان

  • Madhujit Ghosh
  • Jonathan J. Guernsey
  • Devinder Kaur
چکیده

A text parser was used to calculate the statistical distribution of words within an email body. This information was used by a neurofuzzy system to determine the spam classification of the email. This process of detecting spam in an email was experimentally found to be 90% efficient. This design is exceptionally good as compared to present day filters based on its simplicity and limited scope of detection methods. Our system could be further improved by incorporating other identifiers of email spam.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Adaptive Spam Filtering Using Only Naive Bayes Text Classifiers

In the past few years, machine learning and in particular simple Naive Bayes classifiers have proven their value in filtering spam emails. We hereby put Naive Bayes filters to the test, against potentially more elaborate spam filters that will participate in the ceas 2008 challenge. For this purpose, we use the variants of Naive Bayes that have proven more effective in our earlier studies. Furt...

متن کامل

Naive Bayes Spam Filtering Using Word-Position-Based Attributes

This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, have previously been used for this purpose, but the author’s implementation using wordposition-based attribute vectors gave very good results when tested on several publicly available corpora. The effects of various forms o...

متن کامل

Naive Bayes spam filtering using word-position-based attributes and length-sensitive classification thresholds

This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, have previously been used for this purpose, but the author’s implementation using word-position-based attribute vectors gave very good results when tested on several publicly available corpora. The effects of various forms ...

متن کامل

Spam Filtering with Naive Bayes - Which Naive Bayes?

Naive Bayes is very popular in commercial and open-source anti-spam e-mail filters. There are, however, several forms of Naive Bayes, something the anti-spam literature does not always acknowledge. We discuss five different versions of Naive Bayes, and compare them on six new, non-encoded datasets, that contain ham messages of particular Enron users and fresh spam messages. The new datasets, wh...

متن کامل

Evolutionary Symbiotic Feature Selection for Email Spam Detection

This work presents a symbiotic filtering approach enabling the exchange of relevant word features among different users in order to improve local anti-spam filters. The local spam filtering is based on a ContentBased Filtering strategy, where word frequencies are fed into a Naive Bayes learner. Several Evolutionary Algorithms are explored for feature selection, including the proposed symbiotic ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003