Systems and methods for high dimensional 3D data visualization
US11455759B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 21, 2020 |
| Grant date | Sep 27, 2022 |
| Priority date | — |
| Expiry date | Dec 21, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T19/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Data visualization processes can utilize machine learning algorithms applied to visualization data structures to determine visualization parameters that most effectively provide insight into the data, and to suggest meaningful correlations for further investigation by users. In numerous embodiments, data visualization processes can automatically generate parameters that can be used to display the data in ways that will provide enhanced value. For example, dimensions can be chosen to be associated with specific visualization parameters that are easily digestible based on their importance, e.g. with higher value dimensions placed on more easily understood visualization aspects (color, coordinate, size, etc.). In a variety of embodiments, data visualization processes can automatically describe the graph using natural language by identifying regions of interest in the visualization, and generating text using natural language generation processes. As such, data visualization processes can allow for rapid, effective use of voluminous, high dimensional data sets.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.