An information processing method, device, and device
An information processing method and attribute information technology, applied in the field of information processing methods and devices, and equipment, can solve problems such as loss of trust, decline in the reputation of advertising platforms, and damage to the reputation of advertising platforms
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Embodiment 1
[0063] In order to solve the aforementioned technical problems, an embodiment of the present invention provides an information processing method, which is applied to information processing equipment, and the information processing equipment includes various computing equipment with information processing capabilities, such as personal computers, tablet computers, notebooks, etc. Computers, integrated servers, etc. The information processing device in the embodiment of the present invention may specifically be an advertising platform or a computing device on the traffic master side or a third-party detection platform. The program code is invoked by the controller to implement, of course, the program code can be stored in a computer storage medium. It can be seen that the information processing device at least includes a processor and a storage medium.
[0064] figure 2 It is a schematic diagram of the implementation flow of an information processing method in an embodiment of...
Embodiment 2
[0087] Based on the foregoing embodiments, the embodiments of the present invention provide a classification model based on the introduction of machine learning technology, which considers all feature dimensions for each click classification and then makes a comprehensive judgment. In the initial stage of forming the classification model, it is still necessary to manually select as many dimensional feature parameters as possible for machine learning model training, and decide which features to use to describe according to the degree of discrimination of the feature parameters to the training results. There is basically no problem of manual intervention in selecting parameters. , machine learning can learn the appropriate parameters by itself; because the feature meaning is more intuitive than meaningless parameters, it is easier to understand when combined with the distribution of feature data; first, based on the real-time penalty of the machine learning model, the penalty The...
Embodiment 3
[0113] It can be seen from Embodiment 1 and Embodiment 2 that each embodiment of the present invention actually provides a classification method based on machine learning to distinguish whether the click operation of an advertisement is a cheating operation, and the classification of each click operation will consider All feature dimensions are then comprehensively judged. In contrast, the technical solutions provided by the embodiments of the present invention are more intelligent and accurate, and have stronger persuasiveness in the interpretation of results.
[0114] The following describes the training process of the training model. Figure 3A It is a schematic diagram of the training process of the training model of the third embodiment of the invention, as Figure 3A As shown, the process mainly includes:
[0115] Step S301, obtaining various logs;
[0116] Specifically, in the process of implementation, click logs, advertisement exposure logs, effect logs (Trace Log)...
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