Information exchange method and system based on local region characteristic self-learning

Abstract

The invention relates to an information exchange method and system based on local area characteristic self-learning, and the method comprises the steps: setting a local terminal, collecting local information data according to a preset information classification table, storing the local information data in the local terminal, carrying out the screening processing, and storing the data in a local information data private chain block; the public chain block is used for screening and processing the local information data and then storing the local information data into the local information data; receiving a self-learning demand of local area characteristics, linking to a response service block, calling corresponding public data from the public chain block, and establishing a data model based on a neural network according to a strategy requirement of the self-learning demand; and in the response service block, substituting each private data in the private chain block into the data model to obtain corresponding local region characteristic self-learning private recommendation data, and sending the private recommendation data to a corresponding local terminal. According to the method, the information data of the local user can be collected through the local terminal, and the local region characteristic self-learning scheme is generated and pushed.

Description

technical field [0001] The invention relates to the technical field of information exchange, in particular to a method and system for information exchange based on self-learning of local area characteristics. Background technique [0002] With the rapid development of Internet data, communication technologies based on data information analysis have gradually emerged, and people's lives can reflect many information characteristics based on regional, habitual, cultural, etc. The provision of predictive data for subsequent operations has become an important research topic. [0003] Although the local area characteristic information data has certain regularity, it is also very difficult to make accurate use of it, eliminate the invalid data, and form a circularly promoted information flow. For example, in the medical and health field, many intelligent health detection devices have emerged. These health detection devices are collecting and generating a large amount of personal-r...

AI Technical Summary

Problems solved by technology

When the patient's condition is very serious and requires expert consultation, it is necessary to get in touch with various experts and coordinate the time of the experts one by one, which consumes a lot of time, so that the patient's demand for immediate diagnosis cannot be met, and the time for the patient to seek medical treatment is delayed.

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