Method for obtaining APP service feature library and corresponding device
A technology of business features and feature items, applied in the field of big data, can solve the problems of inability to meet DPI identification, private features, feature blind spots, etc., and achieve the effect of improving coverage and applicable scenarios, eliminating data blind spots, and improving accuracy.
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Embodiment 1
[0063] This embodiment provides a method for obtaining an APP service feature library. Using the method for obtaining an APP service feature library in this embodiment, a service feature library with an APP name can be constructed, and the user data of an unknown service type can be processed through the service feature library. The judgment of the APP to which it belongs lays the foundation for analyzing the network behavior of users using the APP on the Internet. The method for obtaining the APP business feature library in this embodiment is applicable to various application scenarios involving APP business feature recognition, for example, in DPI technology, the feature analysis of business data, precise marketing of business data, or analysis of business data to obtain User portraits, etc.
[0064] Such as figure 1 As shown, the method for obtaining the APP service feature library in this embodiment includes the following steps:
[0065] In step 101, an APP installation ...
Embodiment 2
[0146] In an actual application scenario, in the simulated business data generated according to the method of Embodiment 1, there will be a device number of the simulator. Since the number of simulators is limited, there will be a large amount of data containing the same device number in the simulated business data. When performing feature extraction, the device number will be determined as a service feature, which will affect the identification of subsequent user data.
[0147] In order to solve the foregoing problems, this embodiment improves the method in Embodiment 1 to obtain a more accurate service feature database. Among them, most of the implementation process is the same as that of Embodiment 1, and will not be repeated here, and only the areas with improvements will be described below.
[0148] In this embodiment, the learning data set includes a first label data set, a second label data set, and a third label data set; wherein, the establishment process of the first l...
Embodiment 3
[0160] In order to more clearly show the process of establishing the learning data set and the process of establishing the business feature library in the above embodiment 1, combined with Figure 7 and Figure 8 , once again briefly explain the concept and implementation process of the above embodiment.
[0161] Such as Figure 7 As shown, the process of establishing the learning data set is briefly and clearly shown. Obtain the APP installation package, and determine the name of the APP to which the APP installation package belongs, parse the APP installation package, obtain the URL data, label the URL data with the APP name, and establish the first label data set.
[0162] The simulator installs the APP installation package, captures the simulated business data generated by each APP, labels the simulated business data with the APP name, and creates a second label data set.
[0163] Analyze the APP installation package, get the package name, and extract the APP identifier...
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