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Ranking visualization types based upon fitness for visualizing a data set

A data set and data concentration technology, applied in other database browsing/visualization, other database retrieval, digital data information retrieval, etc., can solve problems such as data set difficulties

Active Publication Date: 2014-11-05
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, it is difficult for many users to choose the best visualization type to display their particular data set

Method used

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  • Ranking visualization types based upon fitness for visualizing a data set
  • Ranking visualization types based upon fitness for visualizing a data set
  • Ranking visualization types based upon fitness for visualizing a data set

Examples

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Embodiment Construction

[0017] The following detailed description relates to techniques for arranging visualization types. Although the subject matter described herein is presented in the general context of program modules executing in conjunction with the execution of an operating system and application programs on a computer system, those skilled in the art will recognize that other implementations may be used with other types of program modules. Module combination execution. Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Furthermore, those skilled in the art will appreciate that the subject matter described herein may be used in conjunction with other applications including handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. Practice with other computer system...

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Abstract

Technologies are described herein for ranking visualization types. In order to rank the visualization types, visualization metadata is generated for each of the visualization types and data set metadata is generated for the data set. A suitability score is then computed based upon the visualization metadata and the data set metadata through the use of data mapping rules and chart selection rules. The visualization types are then ranked according to the computed scores. A user interface may then be displayed that includes visual representations corresponding to the visualization types that are ordered according to the ranking. One of the visual representations may then be selected to apply the corresponding visualization type to the data set.

Description

Background technique [0001] Desktop productivity applications often offer many options for visualizing data. For example, a spreadsheet application may allow a user to select a column chart, line chart, pie chart, histogram, area chart, scatter chart, or another type of chart for visualizing the contents of a data set. Each type of graph can be used more or less efficiently to represent the data in a given dataset. As an example, pie charts work well for visualizing certain datasets, while scatterplots do not work well for visualizing the same datasets. [0002] In order to visualize a data set, desktop productivity applications typically require the user to select one of the available visualization types. However, making such a choice is difficult because many users may not know the type of visualization most applicable to their dataset and may not know the scope and extent of their own data. Many users may not yet be aware of all available visualization types, especially ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F3/14G06F17/18G06F15/17
CPCG06F17/30994G06F16/904
Inventor B·L·克龙尼斯特D·P·考瑞D·B·李
Owner MICROSOFT TECH LICENSING LLC