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A method for displaying large-scale multi-attribute stacked histogram in a limited space

A limited space, histogram technology, applied in the field of visualization, can solve the problems of indistinguishable boundaries, columnar visual discontinuity, visual interference, etc., and achieve the effect of improving readability, increasing data display capacity, and wide application

Active Publication Date: 2019-01-25
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The main difficulties are: 1) Due to excessive compression, the boundaries of each column are indistinguishable; 2) Columns of the same color (same numerical attribute) are visually discontinuous, causing serious visual disturbance and confusion

Method used

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  • A method for displaying large-scale multi-attribute stacked histogram in a limited space
  • A method for displaying large-scale multi-attribute stacked histogram in a limited space
  • A method for displaying large-scale multi-attribute stacked histogram in a limited space

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Embodiment Construction

[0039] The purpose and effect of the present invention will become more obvious through an optimization case of a stacked histogram of multi-dimensional housing data and the accompanying drawings.

[0040] Such as figure 1 As shown, the method for displaying a large-scale multi-attribute stacked histogram in a limited space in this embodiment includes the following steps:

[0041] (1) Obtain massive multi-dimensional housing data and initialize it, including standardization and weighted calculation of attributes. The specific steps are as follows:

[0042] 1-1. In the data set, let n be the number of data options, and m be the number of data indicators. Each item of data contains attributes of multiple dimensions, for example: price per unit area c 1 , area c 2 , year of construction c 3, the number of bedrooms c 4 etc., uniformly standardize the attributes of each item of data to the [0, 1] interval.

[0043] Specifically, let c j_max is the maximum value of the jth in...

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Abstract

The invention discloses a method for displaying a large-scale multi-attribute stacked histogram in a limited space, comprising the following steps: (1) acquiring data and initializing the data; (2) sampling according to the initialized data obtained in the step (1) and using an exchange-based heuristic greedy method to minimize the information loss of the multi-option numerical attributes caused by the average sampling; (3) according to the sampled data obtained in the step (2) after the information loss is minimized, using an exchange-based heuristic greedy method to minimize the jitter of multi-option numerical attributes in the sampled stacked histogram; (4) drawing a stacked histogram according to the sample data obtained in the step (3) after the readability is enhanced; The inventioncan help the user to better perceive the stacked histogram of the large-scale multi-attribute data, and discover and analyze the data pattern contained in the visualization, and has the potential ofwide application in the related fields such as large-scale data visualization and visual analysis.

Description

technical field [0001] The invention relates to the field of visualization technology, in particular to a method for displaying a large-scale multi-attribute stacked histogram in a limited space. Background technique [0002] A stacked column chart is a common form of visualization. Each row in the figure represents an option whose value is to be assessed. Each row is stacked by multiple columns whose colors represent different numerical attributes, and whose length represents the value of the corresponding attribute. The stacked column chart can visually display the data of each attribute contained in each option, showing the relationship between the individual and the whole. Stacked histograms are often used to compare the value of different options and at the same time compare the value of different attributes within an option. Compared with ordinary histograms, stacked histograms can show more dimensions of data. [0003] However, stacked histograms are gradually dif...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/26
Inventor 巫英才翁荻陈然邓紫坤
Owner ZHEJIANG UNIV
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