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Method and device for analyzing sequence based on probabilistic graph model

A probabilistic graphical model and sequence-to-sequence technology, applied in probabilistic CAD, character and pattern recognition, instruments, etc., can solve problems such as analysis and achieve the effect of improving applicability and reducing complexity

Active Publication Date: 2022-04-12
ANT YUNCHUANG DIGITAL TECH (BEIJING) CO LTD
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Problems solved by technology

[0003] Traditional index sequence analysis methods usually need to set parameters for each sequence, and cannot analyze irregular cycles (such as monthly cycles). Therefore, it is necessary to provide a more effective sequence analysis method so that it can be simply and efficiently Analysis of indicator series

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  • Method and device for analyzing sequence based on probabilistic graph model
  • Method and device for analyzing sequence based on probabilistic graph model
  • Method and device for analyzing sequence based on probabilistic graph model

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Embodiment Construction

[0027] The solutions provided in this specification will be described below in conjunction with the accompanying drawings.

[0028] As mentioned above, in order to solve practical problems, it is usually necessary to analyze the index sequence (also called the actual value sequence, referring to the sequence formed based on the actual value of the index). The analysis here includes but is not limited to at least one of the following: periodical analysis, outlier removal, noise reduction, peak position determination, and the like. This program mainly describes the periodic analysis.

[0029] Assuming data with minute granularity, and assuming s d (t) Indicates the index value of the t-th minute of the d-th day (hereinafter also referred to as the actual value), then the periodic analysis is to determine the s d (t) Which days are most similar to the index values ​​at the tth minute. In other words, periodicity analysis is to use days as the unit, aiming at which periods ...

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Abstract

The embodiment of the invention provides a method and device for analyzing a sequence based on a probabilistic graph model, in the method for analyzing the sequence, an observation value sequence of an index is obtained, and the observation value sequence comprises D observation values of the index in continuous D time periods. A parameter priori distribution set for the target parameter and an actual value priori distribution set for the actual value of the index are acquired. The target parameters comprise a difference parameter between the observed value and the actual value and D similarity parameters. The ith similarity parameter in the D similarity parameters is used for measuring the similarity of two actual values at an interval of i time periods. Based on the observation value sequence, the parameter priori distribution, and the actual value priori distribution, a probabilistic graph model is constructed, the probabilistic graph model comprising at least D nodes corresponding to D actual values of D periods, and connecting edges between the nodes. And determining a periodic analysis result for the actual value of the index according to the connecting edge in the probability graph model.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer information processing, and in particular to a method and device for analyzing sequences based on a probabilistic graphical model. Background technique [0002] Index sequence refers to the sequence of index values ​​of business indicators arranged in chronological order. In many scenarios, it is necessary to analyze the indicator sequence (for example, periodic analysis) to solve practical problems. For example, in the intelligent operation and maintenance scenario, elastic expansion and contraction can be performed by analyzing the index sequence. Or, by analyzing the index sequence, determine the corresponding peak and baseline, so as to realize the staggered deployment of containers. In addition, using the periodicity analysis results of the indicators, it is also possible to perform time series forecasting, anomaly detection, and so on. [0003] Traditional index sequ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06K9/62G06F111/08
Inventor 余航廖聪胡韵王昕喆李建国
Owner ANT YUNCHUANG DIGITAL TECH (BEIJING) CO LTD
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