Research On Visualization Method Of Radial Tree Based On The Theory Of Attribute Partial Ordered Structure Diagram

As one of data visualization methods, attribute partial ordered structure diagram is developed on the basis of the theory of formal concept analysis. It can transform the internal structure and inner connection of data into graph and realize attribute clustering, then help people extract useful knowledge from data information, it is a useful knowledge discovery method and has been used in many fields now. In order to enrich the expression of partial ordered structure, a new visualization method based on the theory and algorithm of attribute partial ordered structure diagram is proposed in this paper.The article first studied the theory of formal concept analysis and attribute partial ordered structure diagram, programmed to realize the algorithm of attribute partial ordered structure diagram; and introduced hierarchical data visualization methods and point out the advantages and disadvantages of each method to make a comparative analysis, also analyzed the layout of partial ordered structure diagram and chose Radial Tree method to improve the algorithm of partial ordered structure diagram. Then by improving the algorithm based on original algorithm of attribute partial ordered structure diagram, put forward a new visualization approach of partial ordered structure: partial ordered structure radial tree. Finally, introduced the method of partial ordered structure radial tree in detail and programmed to realize its algorithm, applied this new method to some specific examples and built a small visualization system on.Net platform.Partial ordered structure radial tree shows the radial layout instead of the orthogonal layout in attribute partial ordered structure diagram, it uses concentric circles to represent attribute layers and puts all the attributes as well as objects in one circular area in order that it can make better use of space. Then apply the new method to some formal contexts and the result shows that partial ordered structure radial tree can be applied to formal context data visualization, the hierarchical structure of data is intuitionistic, and it can present potential information of data more effectively, thus providing a new approch for further data mining and knowledge discovery.