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Automatic insight discovery method for multi-dimensional time series data

A time series and discovery method technology, applied in the computer field, can solve problems such as inability to find insights accurately and effectively, consume manpower and time, and achieve the effect of avoiding confusion of evaluation standards and improving accuracy and efficiency.

Pending Publication Date: 2021-11-30
北京必示科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In current production practice, engineers discover insights in multi-dimensional time series data through manual analysis. However, because the number of dimension combinations is increasing exponentially, and each search requires a lot of manual operations and judgments, Such a manual analysis process is very labor-intensive and time-consuming
Unable to discover insights accurately and efficiently enough

Method used

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  • Automatic insight discovery method for multi-dimensional time series data
  • Automatic insight discovery method for multi-dimensional time series data
  • Automatic insight discovery method for multi-dimensional time series data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] This embodiment provides an automatic insight discovery method for multi-dimensional time series data, the process is as follows figure 2 shown.

[0039] The method includes the following operations:

[0040] S1 The user specifies a data set and hyperparameters, and the hyperparameters include the maximum search time and the maximum number L of insights. Specifically, the user can specify the path or URI (universal resource identifier, uniform resource locator) of the data source, and the data source can be a certain file (such as a CSV file or an Excel table) or a certain database.

[0041] Optionally, after the user specifies the path or URI of the data source, all fields in the data source are read, and then the user selects which of the following four categories each field belongs to: 1. Timestamp, only one field can be used as Timestamp; 2. Attribute, with at least one field as an attribute; 3. Index, with at least one field as an index. The indicator fields re...

Embodiment 2

[0065] This embodiment provides an automatic insight discovery device for multi-dimensional time series data. The device includes: a receiving module, a searching module, and a display module, wherein:

[0066] A receiving module, configured to receive user-specified data sets and hyperparameters, where the hyperparameters include a maximum search time and a maximum number of insights L;

[0067] The search module is used for the insight-based formalization method and evaluation method, and within a specified search time, searches for L insights that maximize the insight score, and the insight score is used to indicate the degree to which the insight deserves attention;

[0068] The display module is used to visually display the searched L insights to the user.

[0069]Optionally, the specified module is also used to read all the fields in the data source after the user specifies the path or URI of the data source, for the user to select which one of the following four categor...

Embodiment 3

[0080] This embodiment provides a computer device, and the device includes:

[0081] one or more processors;

[0082] storage means for storing one or more programs,

[0083] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any one of the first embodiment.

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Abstract

The invention discloses an automatic insight discovery method for multi-dimensional time series data. The method comprises the steps of S1, specifying a data set and hyper-parameters by a user; S2, searching the insight with the maximum insight score; and S3, visualizing the searched insights and displaying the insights to the user. According to the method and the device, the technical problems that manpower and time costs are consumed and manual operation and judgment are excessively depended when the multi-dimensional time sequence data is manually analyzed are solved, automatic mining of insight of the multi-dimensional time sequence is realized, and the searching efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to an automatic insight discovery method for multi-dimensional time series data. Background technique [0002] At present, various software systems often record events in the system by outputting logs. Each log records an event in the system and a series of fields used to describe the event. These fields are divided into three categories: 1) time; 2) attributes, which represent the characteristics of each event, generally discrete values; 3) indicators, which represent the performance of each event on a certain indicator, generally continuous values. For each attribute combination (a combination of a series of attributes and their values) and each indicator, a time series can be obtained. Such data is called multi-dimensional time series data. Software system development engineers or operation and maintenance engineers Focuses on unusual places in multidimensional tim...

Claims

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Application Information

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IPC IPC(8): G06F16/9537G06F16/9538G06F16/955G06F16/957
Inventor 曹立隋楷心刘大鹏蒋鹏杰
Owner 北京必示科技有限公司
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