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February 18, 2026Open Access

Hierarchical Clustering Taxonomy: Structure, Algorithms, and the Gaps That Shape Modern Data Mining

Iryna Ivchenko Oleh Ivchenko

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Key Points

This research aims to clarify the taxonomy of hierarchical clustering and its algorithms within data mining.
Reviewed existing literature on hierarchical clustering methods.
Analyzed the structure and organization of algorithms.
Identified gaps in current data mining practices.
Outlined various hierarchical clustering techniques and their applications.
Demonstrated the importance of structural understanding in developing effective algorithms.
Highlighted significant gaps that hinder progress in modern data mining.

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Implication

This research article examines hierarchical clustering algorithms in data mining, highlighting structural gaps.

Abstract

Research article: Hierarchical Clustering Taxonomy: Structure, Algorithms, and the Gaps That Shape Modern Data Mining

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Cite This Study

Ivchenko et al. (2026) studied this question.

synapsesocial.com/papers/6997fa90ad1d9b11b3453ee2 https://doi.org/10.5281/zenodo.18683614

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