Data display method based on index tree and terminal equipment

Abstract

The embodiment of the invention discloses a data display method based on an index tree and terminal equipment. A specific embodiment of the method comprises the following steps: receiving a target index input by a user; determining a calculation rule index; determining an analysis method; determining a candidate data sequence based on the target index, the calculation rule index and the analysis method; and determining target data based on the candidate data sequence. According to the implementation mode, the invention includes building indexes of data into an index tree model set; searching a target index tree model according to the index tree model set; and performing causal analysis, fruit cause analysis and bidirectional analysis on the target index tree model by using the determined analysis method. The accuracy of determining the target data can be improved, and the target equipment is controlled to improve the action completion level.

Description

technical field [0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular, to methods for generating and displaying information, and terminal devices. Background technique [0002] Data analysis refers to the use of appropriate statistical analysis methods to analyze a large amount of collected data, summarize them, understand and digest them, in order to maximize the development of data functions and play the role of data. Data analysis is the process of studying and summarizing data in detail in order to extract useful information and form conclusions. By displaying the results of data analysis, it is possible to control external devices to issue warning messages or perform warning actions. In this way, the results of data analysis can be used to display data to assist follow-up tasks and improve the level of completion of follow-up tasks. [0003] However, when data analysis and display is carried out in the above-men...

AI Technical Summary

Problems solved by technology

[0004] First, when the amount of data in the database is huge, it takes a lot of time to find and determine the relationship between the data and the accuracy is very low, resulting in inaccurate judgments on the relevant factors affecting the target data and the factors affected by the target data, that is, the target data

[0005] Second, traditional data analysis methods generally perform causal analysis, that is, they can only find the results affected by the target data, but they cannot reversely analyze and judge the relationship between the data, and cannot handle complex data analysis. The level of data analysis is lowered, resulting in low accuracy in finding target data

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