Method and device for identifying spam
A spam information and information identification technology, applied in the field of information processing, can solve the problems of inaccurate identification results and human resource consumption, and achieve the effects of improving timeliness, improving grasping ability, and reducing accuracy
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Embodiment 1
[0034] Embodiment 1 of the present application provides a spam identification method, specifically, as figure 1 As shown, it is a flow chart of the steps of the method described in Embodiment 1 of the present application, and the method may include the following steps:
[0035] Step 101: Determine the training sample set, the information category to which each training sample in the training sample set belongs, and the basic feature data of each training sample.
[0036] It should be noted that in machine learning, the data composition of the training sample set is very important, and the distribution of positive and negative samples should be as close as possible to the data distribution of the real environment in order to make the recognition model more robust in the real environment. Stickiness and higher accuracy. Therefore, in the training sample set, the ratio of the number of spam training samples to the number of non-spam training samples can usually be within a set r...
Embodiment 2
[0108] Based on the same inventive concept, Embodiment 2 of the present application provides an information identification device, specifically, as image 3 As shown, it is a schematic structural diagram of the device described in Embodiment 2 of the present application, and the device may include:
[0109] A sample determination unit 301, configured to determine the training sample set, the information category to which each training sample in the training sample set belongs, and the basic feature data of each training sample;
[0110] A model learning unit 302, configured to train an information recognition model for identifying spam according to the information category to which each training sample belongs and the basic feature data of each training sample;
[0111] The spam identification unit 303 is configured to classify each piece of information to be identified based on the obtained information identification model, and determine whether each piece of information to b...
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