Message processing method and electronic device

Abstract

The invention discloses a message processing method applied to an electronic device. The method comprises the steps that the electronic device can acquire a junk message sample database, and when receiving a message, the electronic device judges whether the message is a junk message or not according to a first predetermined rule; when the electronic device judges that the message is not the junk message according to the first predetermined rule, the electronic device matches the message with junk message samples in the junk message sample database and judges whether a matching result meets the requirement of a second predetermined rule or not; when matching is not successful, whether the message is the junk message or not is judged according to a third predetermined rule. By means of the method, the technical problem that in the prior art, the filtering accuracy of junk message is limited is solved, and the technical advantage of improving the filtering accuracy of the junk message is achieved.

Description

technical field [0001] The invention relates to the field of electronic technology, in particular to an information processing method and electronic equipment. Background technique [0002] Spam filtering is the application of natural language processing technology to filter text messages containing deception, pornography, advertisements, etc. received by mobile phones and other instant messaging software. [0003] From the point of view of whether the content of information is legal, spam can be divided into illegal spam and common spam. The types of illegal spam information include fraud, pornographic services, invoices, etc. In order to avoid being filtered by the keyword filtering system, this type of spam information usually adopts variants for key words appearing in the information. For example, the variant of "invoice" is "fa\ ticket\". Ordinary spam mainly includes real estate advertisements, operator push information, business promotion information, etc. This type...

AI Technical Summary

Problems solved by technology

[0005] It is difficult to avoid frequent combinations of natural language by filtering keywords that appear in spam; to filter text based on the lexical and grammatical features of the text, it is difficult to filter out spam that does not contain obvious grammatical features; the scale of required data resources is large, It is difficult to deploy directly to the mobile client, and the information needs to be uploaded to the server for filtering, which has the risk of leaking user privacy

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