The keyword combination strategy is an efficient means of managing spam

such as spam messages

and RCS. The current strategy relies mainly on manual methods for preparation and maintenance. Due to the need to analyze a large amount of spam

the workload is heavy. This paper proposes an automatic AIbased strategy generation method

which can assist manual analysis of spam information and keyword combination strategy generation

thus greatly reducing manpower. Specifically

in this paper

the words in the spam are matrixed according to specific rules to form a keyword matrix

and input into a classifier based on a two-dimensional convolutional neural network for training. This translates the keyword extraction problem into a convolution operation in the keyword matrix. By training the classifier

the convolutional network can automatically extract the key combination features with significant category features. By extracting arbitrary information

the information can be found by extracting the convolution window that can maximize the convolution network activation value. The most appropriate keyword combination strategy. Experiments show that the keyword combination strategy generated by the algorithm has a good precision and recall.