ChatGPT as an Artificial Intelligence Tool to Provide an Analytical Boost to Text Mining: An Application to Tucker Models for Multiway Tables

In this comprehensive study, we meticulously investigated multidimensional data analysis techniques, particularly focusing on Tucker decomposition methods, spanning the period from 2000 to 2025. Our primary objective was to discern trends, advancements, and applications of these techniques across various domains of knowledge and how they have evolved over time. An extensive corpus of 288 scientific articles related to tensor decompositions, Tucker models, and applications was previously reviewed. Multivariate methods such as text mining using IraMuteq software and MANOVA-Biplot were employed to visualize identified data patterns, and the analytical capability of ChatGPT artificial intelligence was assessed to provide contextual insights and add another layer of information to the research. Our conclusions underscore the importance of blending traditional statistical approaches with natural language processing prowess to achieve a profound understanding of the data. This analysis offers a comprehensive perspective on the evolution and application of multidimensional data analysis techniques, with a special emphasis on the enduring relevance of Tucker techniques in this new millennium. Received: 24 July 2025 | Revised: 22 May 2026 | Accepted: 10 June 2026 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Roberto Cascante-Yarlequé: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing –riginal draft, Writing – review & editing, Visualization, Supervision, Project administration. Purificación Galindo-Villardón: Software, Validation, Formal analysis, Resources, Data curation, Writing – review & editing. Fabricio Guevara-Viejó: Software, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing.

Authors

Publication Details

Journal
Journal of Computational and Cognitive Engineering
Published
2026-07-28
DOI
https://doi.org/10.47852/bonviewjcce62026916
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ChatGPT as an Artificial Intelligence Tool to Provide an Analytical Boost to Text Mining: An Application to Tucker Models for Multiway Tables

Purificación Galindo‐Villardón, Fabricio Guevara-Viejó, Roberto Cascante-Yarlequé
Journal of Computational and Cognitive Engineering
Machine Learning in Healthcare
article

ChatGPT as an Artificial Intelligence Tool to Provide an Analytical Boost to Text Mining: An Application to Tucker Models for Multiway Tables

Purificación Galindo‐Villardón, Fabricio Guevara-Viejó, Roberto Cascante-Yarlequé
article en

Abstract

In this comprehensive study, we meticulously investigated multidimensional data analysis techniques, particularly focusing on Tucker decomposition methods, spanning the period from 2000 to 2025. Our primary objective was to discern trends, advancements, and applications of these techniques across various domains of knowledge and how they have evolved over time. An extensive corpus of 288 scientific articles related to tensor decompositions, Tucker models, and applications was previously reviewed. Multivariate methods such as text mining using IraMuteq software and MANOVA-Biplot were employed to visualize identified data patterns, and the analytical capability of ChatGPT artificial intelligence was assessed to provide contextual insights and add another layer of information to the research. Our conclusions underscore the importance of blending traditional statistical approaches with natural language processing prowess to achieve a profound understanding of the data. This analysis offers a comprehensive perspective on the evolution and application of multidimensional data analysis techniques, with a special emphasis on the enduring relevance of Tucker techniques in this new millennium. Received: 24 July 2025 | Revised: 22 May 2026 | Accepted: 10 June 2026 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Roberto Cascante-Yarlequé: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing –riginal draft, Writing – review & editing, Visualization, Supervision, Project administration. Purificación Galindo-Villardón: Software, Validation, Formal analysis, Resources, Data curation, Writing – review & editing. Fabricio Guevara-Viejó: Software, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review & editing.

Journal of Computational and Cognitive Engineering
Openalex Percentile: Top 99%
Machine Learning in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ChatGPT as an Artificial Intelligence Tool to Provide an Analytical Boost to Text Mining: An Application to Tucker Models for Multiway Tables — Purificación Galindo‐Villardón, Fabricio Guevara-Viejó, et al. · Journal of Computational and Cognitive Engineering (2026) | TGRS Research Map | TGRS