Junk mail detection method and system based on dynamic update of categorizer

Abstract

The invention relates to a method and a system for detecting junk mails based on the dynamic updating of a sorter, which includes the following steps: the sorter composed of class vector is constructed; the degree of similarity between the characteristic vector and each class vector of the mail to be detected is acquired; the class vector with the highest degree of similarity is sorted; the classification fed by the user on the mail to be detected is acquired; the times of carrying out correct classification of each class vector is counted; the new mail is received and sorted according to the steps and the sorter is updated when the set conditions are met, the class vector is reserved when the correct sorting times exceeds the set value, and the newly-received mail to be detected is sorted; the system includes a sorter updating unit, the sorter is updated when the set conditions are met, the class vector is reserved for participating mail classification in the future when the correct sorting times exceeds the set value. The invention reserves the class vector with good classification effect in the sorter for a period of time, which guarantees the accuracy of the classification and cannot be affected by the limitation of the new a data stream.

Description

technical field [0001] The invention relates to the technical field of e-mail processing, in particular to a spam detection method and system based on classifier dynamic update. Background technique [0002] With the increasing popularity of the Internet, e-mail has become an important medium of daily communication and one of the most convenient means of communication for everyone, basically replacing traditional paper letters, and people are increasingly relying on It and can't do without it. However, the emergence of electronic spam has caused a growing problem, seriously threatening people's normal email communication. The expansion of spam not only wastes a lot of storage space and communication bandwidth, but also consumes a lot of user time to process and delete them. Therefore, it is very necessary and meaningful to study the detection and filtering methods of this kind of spam. [0003] Spam classification detection is essentially a pattern recognition problem. T...

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Problems solved by technology

[0008] From the above analysis, it can be concluded that in the prior art spam classifier update method, the newly received data is used to dynamically update the classifier, which can reflect the changes of the continuously received new data stream and reflect the characteristics of the new data stream, but Since the update process deletes all historical classification vectors, some classification vectors with good classification effects cannot be saved, so the accuracy of the resulting classification is often affected by the limitations of the new data stream

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