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 time...

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Main Author: J. Piatkowski
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9069220/
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spelling doaj-bbe3458854724219b937fbaa17e38bc12021-03-30T01:43:43ZengIEEEIEEE Access2169-35362020-01-018740837409210.1109/ACCESS.2020.29883589069220The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data DependenciesJ. Piatkowski0https://orcid.org/0000-0002-5243-050XDepartment of Computer Science, Czestochowa University of Technology, Czestochowa, PolandIn 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.https://ieeexplore.ieee.org/document/9069220/Data processingdata visualizationinformation analysistree data structuresC$++$ templatesgeneric programming
collection DOAJ
language English
format Article
sources DOAJ
author J. Piatkowski
spellingShingle J. Piatkowski
The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
IEEE Access
Data processing
data visualization
information analysis
tree data structures
C$++$ templates
generic programming
author_facet J. Piatkowski
author_sort J. Piatkowski
title The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
title_short The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
title_full The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
title_fullStr The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
title_full_unstemmed The Conditional Multiway Mapped Tree: Modeling and Analysis of Hierarchical Data Dependencies
title_sort conditional multiway mapped tree: modeling and analysis of hierarchical data dependencies
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description 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.
topic Data processing
data visualization
information analysis
tree data structures
C$++$ templates
generic programming
url https://ieeexplore.ieee.org/document/9069220/
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