3D Virtual Reality Data Mining Visualization
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Solution Overview
Problem
Traditional data mining and visualization methods are inadequate for handling large-scale, multi-dimensional data sets, particularly in fields like patent research, as they often result in missed relevant information and ineffective trend understanding due to the complexity of data representation in two-dimensional formats.
Innovation Solution
A system and method for visual data mining using a 3D virtual or augmented reality space, where multidimensional data is displayed as graphical objects in a 3D environment, allowing users to interact and visualize data in a more intuitive and insightful manner, leveraging machine learning and statistical methods for trend prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is visualized in traditional two-dimensional formats, then the visualization method is simple and easy to implement, but the effectiveness of data comprehension and trend understanding deteriorates due to the complexity of large-scale multi-dimensional data
Solution Approach 1:
The patent transitions from two-dimensional data visualization to three-dimensional virtual reality space, allowing multidimensional data to be represented spatially. This dimensionality change enables users to perceive complex relationships and trends that cannot be effectively displayed in traditional flat formats, directly addressing the limitation of 2D visualization for big data.
2Measurement precision
If patent searching uses traditional search engines with tabular results, then the search process is systematic, but the accuracy of finding relevant prior art deteriorates due to the difficulty of comprehending large amounts of data
Solution Approach 1:
The patent employs color coding to represent different attributes and relationships of patent data in the 3D visualization. This visual encoding allows users to quickly distinguish and comprehend different types of information without having to read and analyze extensive tabular data, thereby improving both accuracy of identification and ease of operation.
Solution Approach 2:
By moving from tabular 2D results to 3D spatial visualization, the system enables users to perceive relationships and patterns in patent data more intuitively. The spatial arrangement of data points in three dimensions makes it easier to identify relevant prior art among large datasets.
3Productivity
If large-scale data is processed using conventional methods, then the processing framework is established, but the productivity of data research deteriorates due to the difficulty of identifying relevant information and trends
Solution Approach 1:
The patent replaces traditional mechanical search and analysis methods with an immersive 3D virtual reality visualization system. This substitution allows researchers to interactively explore and analyze patent data in a spatial environment, significantly improving the efficiency of identifying relevant information and trends compared to conventional linear processing methods.
Data Source
AI summary
Disclosed are methods and systems that help to visualize large groups of documents in a virtual reality or augmented reality environment comprising a three-dimensional (3D) space. An example method involves a computing device: determining a group of elements based at least in part on the one or more input parameters; determining one or more attributes based at least in part on the one or more parameters, the group of elements, or both; determining, for each element from the group, a respective location in a 3D space, based on one or more of the attributes; displaying a 3D graphical environment representing the 3D space, wherein each element from the group is represented in the 3D graphical environment by a graphic object at its respectively determined location in the 3D space; and enabling user interaction with the graphic objects in the 3D graphical environment.