Multi-source heterogeneous data cloud pushing method
A multi-source heterogeneous data and data technology, applied in structured data retrieval, electronic digital data processing, database management systems, etc., can solve problems such as inability to solve multi-source heterogeneous data push
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Embodiment 1
[0094] refer to Figure 1 to Figure 8 , a cloud push method for multi-source heterogeneous data, comprising the following steps:
[0095] Step 1: Design the cloud push platform, and analyze each functional module in the platform. The function design of the cloud push platform is as follows: figure 1 shown
[0096] 1.1 The cloud push platform can push three types of messages: notifications, transparent messages and rich media. The notification is to push the notification message displayed in the system notification bar to the mobile terminal. Pass-through message refers to sending customized content to the client in a pass-through manner. Developers can pre-set rules on the client side to customize messages. Rich media refers to pushing information in the form of pictures, videos, audios, URLs, etc.
[0097] 1.2 The cloud push platform should also support pushing messages to all users or to specific user groups according to label classification, group users according to th...
Embodiment 2
[0160] The present invention provides a cloud push method for multi-source heterogeneous data, which is applied to the two major platforms of Android and iOS, including the following steps:
[0161] Step 1: The cloud push method is used on Android and iOS platforms.
[0162] 1.1 The present invention uses the cloud push platform to test in Android and iOS. The cloud data comes from the performance system, salary system and micro film and television system. After the data is collected, the main component value weight of the data is: user authority, user login time, The mode of user publishing / subscribing (one-to-many / one-to-one), the number of user logins, and the amount of transmitted data. The weight μ is determined after comprehensive consideration, assuming that the component value weights in this system are (0.3, 0.2, 0.2, 0.1, 0.1, 0.1). The higher the weight, the greater the impact of the change of the component value on the final MDCP push result. Since the data comes...
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