Method and system for supporting large-scale time series data interaction based on line segment KD tree

A time-series data and interactive method technology, applied in the field of data visualization, can solve the problems that users cannot learn detailed trend information from it, and affect users' data analysis and cognitive work.

Active Publication Date: 2021-10-22
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method can effectively provide users with insight into the overall data distribution, users cannot get detailed trend information of one or more lines from it.
Therefore, this method will also affect the user's analysis and cognitive work on the data.

Method used

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  • Method and system for supporting large-scale time series data interaction based on line segment KD tree
  • Method and system for supporting large-scale time series data interaction based on line segment KD tree
  • Method and system for supporting large-scale time series data interaction based on line segment KD tree

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0047] This implementation provides an interactive exploration method that supports large-scale time series data based on line segment KD tree;

[0048] figure 1 It is a flow chart of the index construction process in the present invention. The index construction method based on line segment KD tree, including:

[0049] Step 1: For the input time series data p 1 ,...,p m Perform curve segmentation based on the Ramer-Douglas-Peucker method to obtain approximate straight line segments for all time series data. The specific description is: initialize a polyline segment, which only contains the first and last endpoints p of the time series data 1 ,p m ;For a polyline segment, recursively add the farthest point p to the current polyline i , until the distance between all uninserted points and the current polyline is less than a set threshold ∈;

[0050] Step 2: Construct the segment-based KD tree for the segmented segments. The specific description is: first calculate the c...

Embodiment 2

[0069] From the user client, an interactive exploration system for time series data is provided, including:

[0070] The data module is used to select and upload the data content used; set the details of the data field used for visualization; and export the detailed information of the chart or data generated by the analysis in the system;

[0071] Configuration management module, used to set specific visualization parameters; select interactive query tools for visual analysis;

[0072] The statistical information module is used to display the statistical information of the currently selected interactive data; display representative line information; adjust the calculation method of the current interactive query result; adjust or delete the selected range of the interactive query;

[0073] The visualization module is used to display the visual information chart based on the configuration selected by the user; it supports the use of interactive query tools for visual analysis on...

Embodiment 3

[0075] A line-segment KD tree-based system that supports large-scale time series data interaction, including:

[0076] A segmentation module configured to divide each time series into a plurality of line segments, and calculate the slope corresponding to each line segment;

[0077] The KD tree index structure building module is configured to establish a KD tree index structure in three-dimensional space for all line segments after segmentation;

[0078] A calculation module configured to calculate the spatial span information in each KD tree node;

[0079] The query module is configured to, for the interactive target area, query all line segment information passing through the selected area in the KD tree index structure, and perform interactive query.

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Abstract

The invention provides a method for supporting large-scale time sequence data interaction based on a line segment KD tree, and the method comprises the steps of segmenting each time sequence into a plurality of line segments, and calculating the slope corresponding to each line segment; establishing a KD tree index structure in a three-dimensional space for all segmented line segments; calculating spatial span information in each KD tree node; and for the interaction target region, querying all line segment information passing through the selected region in the KD tree index structure, and carrying out interactive query. According to the invention, the problem of difficult query in current large-scale data analysis is effectively solved, and user observation is facilitated.

Description

technical field [0001] The invention belongs to the technical field of data visualization, and in particular relates to a method and system for supporting large-scale time series data interaction based on a line segment KD tree. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] At present, more and more time series data are collected, stored and analyzed, and are involved in many fields, such as finance, health, urban informatics, etc. To gain insight into this time-series data, analysts often need to explore, compare, and correlate data generated by multiple entities. The amount of these data ranges from tens to millions. Therefore, there is a great need for analytical systems that can scale to interactive exploration of large-scale time-series data. [0004] There are many existing exploration methods, and the following is a brief summa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/22G06F16/2458G06F16/248
CPCG06F16/2246G06F16/2474G06F16/248Y02D10/00
Inventor 汪云海赵跃张烜
Owner SHANDONG UNIV
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