For the mankind the grouping of the animals or plants was significant in surviving at the dawn of history (I mean here the poisonous plants or the dangerous animals), and as well as in the area of biology.
Based on some property we are able to create groups of the surrounding objects by simply observing them. But in case we want to create the groups based on too many attributes then we have to apply the methods of computational statistics and by doing so we are able to show the results graphically and effectively. Henceforth I mean the groups as clusters, and the method as cluster analysis.
The main objective of my thesis was to create a software that able to read a database, and according to the inputs it can group the writings, and maybe to show those results or ties that cannot be discovered by historians. The two major trends of the cluster analysis have been implemented in my software, which can be used for examining these ties from various way, and with the help of the figures we can visualize them. Furthermore, the program is capable of showing the shady datapoints by marking obviously their uncertain identification to their group.
The program is flexible in the sense that it can evaluate the results of a poll as well. This is one example that way the program can be developed in the future.