Abstract
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.
Highlights
In computer science, trees are considered as one of the most important abstract data types. They are a subclass of more general, nonlinear graph data structures [1] and are used everywhere where the hierarchical relationships among data elements are present [2]
Other examples of the use of trees can be found in work related to signal reconstruction from a limited number of measurements [7] and to implementation of the tree-dependency oriented technique to automatically generate search query candidates in fetching related questions from the knowledge bases of a Community Question-Answering platforms [8]
Publications, the generic programming paradigm has been used for the implementation of trees, but in the vast majority of cases, these are solutions based only on type parametrization
Summary
Trees are considered as one of the most important abstract data types. Publications, the generic programming paradigm has been used for the implementation of trees, but in the vast majority of cases, these are solutions based only on type parametrization This approach is undoubtedly very convenient and effective, but may not be sufficient and require interference with the previously created code when there is a need to change the rules defining the relationships between nodes. The main focus has been put on providing easy-to-use tools for the construction of multiway trees and to extract additional, often hidden information contained in the processed data.
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