A continuous data optimization method and system based on geographic correlation

Abstract

The invention discloses a continuous data optimization method and system based on geographic correlation, including: determining the initialization weight of the data provider by using the historical data provided by the data provider including a certain target object and the known truth data of the target object ; Calculate the correlation between the target object and other target objects at the current moment; Calculate the aggregate truth of the target object at the current moment; Aggregate the truth of the target object, calculate the credibility, and update the weight of the data provider according to the credibility. Advantages: The present invention adopts the continuous data optimization method based on geographical correlation, which effectively solves the problem that the accurate aggregate truth cannot be obtained when the target object does not collect enough data; the present invention is not enough for the data provided by the data provider. It can greatly improve the accuracy of the results and meet the requirements of truth aggregation.

Description

technical field [0001] The invention relates to a continuous data optimization method and system based on geographic correlation, and belongs to the technical field of artificial intelligence. Background technique [0002] In the information age, with the development of social platforms, there are more and more data providers, and the data they provide is also diverse. However, it is not reliable to obtain the truth from only a single data source due to the elusive authority of the information provided by the data provider. Therefore, in order to obtain more accurate results, it is usually necessary to aggregate data from multiple data providers to obtain the truth. [0003] However, the existing methods of multi-channel information aggregation have shortcomings for some applications. If the traditional truth aggregation method is adopted without considering the geographical correlation of the target object, when only a small amount of data can be collected for a target ob...

AI Technical Summary

Problems solved by technology

[0003] However, the existing methods of multi-channel information aggregation have shortcomings for the application in some fields

If the traditional truth aggregation method is adopted without considering the geographical correlation of the target object, when only a small amount of data can be collected for a target object, the purpose of multi-channel aggregation cannot be achieved, and the final aggregation result will also be inaccurate

[0004] In addition, if only the continuity of the data is considered, when the rate of change of the data is very large, only the aggregation value of the target object at the previous moment is considered as the truth at the current moment, and it is obvious that accurate results cannot be obtained

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