Spam short message identification method and device
A spam text message and identification method technology, which is applied in the field of network management, can solve the problems of poor identification accuracy of spam text messages, high false blocking rate and missed block rate of spam text messages
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Embodiment 1
[0024] Embodiment of the present invention one here proposes the spam text recognition method, as figure 1 As shown, the specific processing flow is as follows:
[0025] Step 11, obtaining the short message to be detected transmitted in the communication system.
[0026] Step 12, for each obtained short message to be detected, determine the terminal number for sending the short message to be detected.
[0027] Wherein, the terminal number may be, but not limited to, a subscriber identity module (SIM, Subscriber Identity Module) card number installed in the terminal, a device identification number of the terminal, or a network access permission number of the terminal. Preferably, in order to improve user perception, in the technical solution proposed here in the embodiment of the present invention, the terminal number is a SIM card number.
[0028] Step 13: According to the determined terminal number, it is judged whether the terminal number belongs to the blacklist of termin...
Embodiment 2
[0050] Embodiment 2 of the present invention Here, on the basis of the above-mentioned embodiment 1, the technical solution proposed here in the embodiment of the present invention is combined with the spam short message monitoring platform in the prior art to realize spam short message identification, such as image 3 As shown, Embodiment 2 of the present invention proposes a spam short message identification system, which mainly includes a spam short message identification model, a spam short message monitoring platform, a customer service center, and a BOSS service system.
[0051] Among them, in the specific implementation, it is necessary to establish a spam SMS identification model, and the established spam SMS identification model outputs a blacklist belonging to the terminal numbers suspected of sending spam messages and a white list of terminal numbers suspected of sending other SMS messages. The list is output to the spam SMS monitoring platform. Subsequent spam SMS ...
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