BAYESIAN SURETY CHECK TO REDUCE FALSE POSITIVES IN FILTERING OF CONTENT IN NON-TRAINED LANGUAGES

摘要

PROBLEM TO BE SOLVED: To reduce false positives by using the surety check of Bayesian spam e-mail filtering, when processing an e-mail of a non-trained language.;SOLUTION: A Bayesian spam filter determines an amount of content in incoming e-mail messages that it knows from learning. If the filter is familiar with a threshold amount of the content, the filter proceeds to classify the e-mail message as being spam or legitimate. Meanwhile, if not enough of the words in the e-mail are known to the filter from training, the filter cannot accurately determine whether the message is a spam. In this case, the filter classifies the message as being of an unknown type. Different threshold metrics can be used, such as the percentage of known words, and the percentage of maximum correction value used during processing. This significantly improves the processing of e-mail, in languages which the filter has not learned.;COPYRIGHT: (C)2009,JPO&INPIT