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Ordination-based verification of feature selection in pattern evolution research

INTELLIGENT DATA ANALYSIS 2024年第4期28卷 891-907页

作者： Hosszu, Gabor Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Electron Devices H-1111 Budapest Hungary

This article explains the idea of pattern systems that develop gradually. These systems involve symbolic communication that includes symbols, syntax, and layout rules. Some pattern systems change over time, like historical scripts. The scientific study of pattern systems is called pattern evolution research, and scriptinformatics is concerned with the modelling of the evolution of scripts. The symbol series consists of symbols from a pattern system, while the graph sequence is a symbol sequence applied with a specific technology. This article describes a method for examining tested pattern systems to confirm their classification, which focuses on more ancient features. The method's effectiveness was tested on Rovash scripts and graph sequences. Multivariate analysis was carried out by using PAST4 software, employing principal coordinates analysis ordination and k-means clustering algorithms.

关键词： Feature selection k-means machine learning principal coordinates analysis scriptinformatics

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Validation of graph sequence clusters through multivariate analysis: application to Rovash scripts

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HERITAGE SCIENCE 2024年第1期12卷 110页

作者： Hosszu, Gabor Budapest Univ Technol & Econ Dept Electron Devices H-1111 Budapest Hungary

This paper introduces the concept of pattern systems that evolve, with a focus on scripts, a specific type of pattern system. The study analyses the development of different script systems, known as scriptinformatics, with a focus on the historical Rovash scripts used in the Eurasian steppe. The aim is to assess the traditional classification of historical inscriptions, referred to as script relics, into distinct Rovash scripts. Clustering and ordination techniques were used to perform multivariate analyses on Rovash scripts and inscriptions. The study presents two new measures, the script-specific holophyletic index and the joint holophyletic index, for evaluating trees produced by hierarchical clustering. The results indicate that holophyletic indices can validate the traditional assignment of inscriptions to scripts through phylogenetic tree evaluation. This method can be extended to include pattern systems with evolutionary properties and graph sequences derived from them, as well as additional scripts and inscriptions.

关键词： Hierarchical clustering Ordination Pattern system Phylogenetic inference Principal component analysis scriptinformatics

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Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques

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INFORMATION 2024年第11期15卷 696页

作者： Salman, Osama A. Hosszu, Gabor Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Electron Devices Muegyetem Rkp 3 H-1111 Budapest Hungary

The purpose of this paper is to describe a feature selection algorithm and its application to enhance the accuracy of the reconstruction of phylogenetic trees by improving the efficiency of tree construction. Applying machine learning models for Arabic and Aramaic scripts, such as deep neural networks (DNNs), support vector machines (SVMs), and random forests (RFs), each model was used to compare the phylogenies. The methodology was applied to a dataset containing Arabic and Aramaic scripts, demonstrating its relevance in a range of phylogenetic analyses. The results emphasize that feature selection by DNNs, their essential role, outperforms other models in terms of area under the curve (AUC) and equal error rate (EER) across various datasets and fold sizes. Furthermore, both SVM and RF models are valuable for understanding the strengths and limitations of these approaches in the context of phylogenetic analysis This method not only simplifies the tree structures but also enhances their Consistency Index values. Therefore, they offer a robust framework for evolutionary studies. The findings highlight the application of machine learning in phylogenetics, suggesting a path toward accurate and efficient evolutionary analyses and enabling a deeper understanding of evolutionary relationships.

关键词： feature selection hyperparameters machine learning phylogenetics scriptinformatics consistency index (CI) false rejection rate (FRR) false acceptance rate (FAR) classification

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Phylogenetic modelling scripts for identifying script versions

Phylogenetic modelling scripts for identifying script versio...

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2023 International Conference on ENTERprise Information Systems, CENTERIS 2023 - International Conference on Project MANagement, ProjMAN 2023 - International Conference on Health and Social Care Information Systems and Technologies, HCist 2023

作者： Salman, Osama A. Hosszu, Gabor Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Electron Devices Muegyetem rkp. 3 BudapestH-1111 Hungary

As the digital and physical worlds connect, machine-learning tools are increasingly being used by businesses and institutions, including archaeological research institutes and museums. The article presents research that, based on the evolution of human scripts, provides a tool for identifying script variants used in old manuscripts and stone inscriptions. This makes the work of paleography institutes and individual researchers more efficient. Using this research, it is possible to provide some information about millions of hitherto unidentified inscriptions using machine learning. The developed and tested method applies the biological phylogenetics tool to script evolution, an area that has yet to be investigated with machine learning tools. The final aim of the research is to use these tools to clarify the connections between many Arabic, Aramaic and Central Iranian script variants. The described procedure gives a new solution to one of the fundamental issues of phylogenetic analysis, feature selection, the effectiveness of which is verified with test runs. The paper presents a new feature selection method to identify the strength or effect of features before phylogenetic processing. This type of dimensionality reduction removes unnecessary features from the dataset for these analyses and interpretations. The method was applied to some versions of Arabic, Aramaic and Middle Iranian scripts, but the procedure is not script-specific. © 2024 The Author(s). Published by Elsevier B.V.

关键词： Arabic Script Aramaic Script Family Clustering Machine Learning Middle Iranian Script Family Phylogenetics Script Identification scriptinformatics

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Phylogenetic modelling scripts for identifying script versions

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Procedia Computer Science 2024年 239卷 1417-1424页

作者： Osama A. Salman Gábor Hosszú Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Electron Devices Műegyetem rkp. 3 Budapest H-1111 Hungary

关键词： Arabic Script Aramaic Script Family Clustering Machine Learning Middle Iranian Script Family Phylogenetics Script Identification scriptinformatics

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