The Research And Application Of Multi-dimensional Data Visualization Analysis Method

In many areas of computer science, it has become a very important issue to handle multi-dimensional data.The birth of visualization technology allows data information to transfer into intuitive physical phenomena or physical quantity, displayed in the form of graphic image and changed with spatial and time variation and presented to the researchers, so that we discover and understand the potential objects or phenomena previously unknown. So the multi-dimensional data visualization become a hot research content of information visualization field.In the course of this study, firstly the visualization technology and the common methods of multi-dimensional data visualization were analyzed and studied. The study discussed the basic principle, advantages and disadvantages and applications of parallel coordinate methodology-the popular improved multi-dimensional data visualization method. It focused on visualization interaction technology and cluster analysis based on parallel coordinate methodology and presented a cluster-based parallel coordinate visualization analysis methodology according to the existing technology, and realized a Responsible Consumer Statistical Analysis System by applying the abovementioned methodology.Finally, this paper proposed the specific design plan and the function realization of the Responsible Consumer Statistical Analysis System. The content of Responsible Consumer Statistical Analysis is multi-dimensional, and users can dynamically change the contents of comparative analysis, display data from multiple angles and sides, and access to results fast, conveniently and accurately. The system enables to display multi-dimensional data by cluster-based parallel coordinate visualization analysis methodology, allowing users to analyze and understand data from many sides and obtain the required visualization results through the simple human-computer interaction process. Users can observe and analyze data more conveniently to access to effective information, greatly reducing the workload.