The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies

In many areas of scientific studies, the processed data show hierarchical dependencies and can be arranged in various tree structures. The shape of such structures depends mainly on the rules defining the ways to organize or systematize the data. Often there is a need to modify these rules many times. In the presented work, the model of the Conditional Multiway Mapped Tree (CMMTree) is proposed. This model was developed to obtain two fundamental functionalities. The first was the possibility to build any tree structures that reflect any relationships between the input data elements, assuming that the model should be able to operate on different types of data and that the node connection rules can be easily changed. The second was the ability to quickly identify the characteristic places that determine the shape of trees, including trees that can contain tens of millions of nodes, and also the ability to quickly reach precisely selected fragments of these trees. To generalize the proposed model the generic programming technique, in C++ language, was used.