Enhanced Bayesian spam filter technique employing LCS

In this growing age of faster communication email became a convenient option for our everyday life. But it cannot be denied that spam mails became greater thread for us. In our work we have discussed about existing spam filtering techniques, at the same time propose a method to make an efficient filter. Bayesian Spam filter is one of the mostly known content based filter, but it also fails when spammer makes intentional spelling mistakes. Our goal of this research was to identify the probable misspelled words and count them like a normal Bayesian filter does. In this research we got more efficiency over a normal spam filter. But it is true that more sophisticated calculation during spam identification could hike the efficiency more than we got.