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TRUNC: A Transfer Learning Unsupervised Network for Data Clustering

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Distributed Computing and Artificial Intelligence, 21st International Conference (DCAI 2024)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1259))

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Abstract

Clustering aims to group similar data objects together while keeping dissimilar objects apart. Various bioinspired algorithms have been developed to address different challenges in clustering tasks. One promising approach is the use of self-organizing neural networks, which can adapt and learn the underlying patterns in the data. Transfer Learning (TL) has also gained attention for its ability to leverage knowledge from one domain to improve learning in another. In this context, a Transfer Learning Unsupervised Network (TRUNC) is proposed, integrating a self-organizing network with TL to enhance clustering performance. This paper introduces TRUNC, presents a sensitivity analysis of the algorithm to the transfer learning term, and an evaluation of its effectiveness when applied to synthetic data.

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Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior of Brasil (CAPES). Finance Code 001 and Grant 2021/11905-0 of the São Paulo Research Foundation (FAPESP).

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Authors and Affiliations

  1. Graduate Program in Technology, Universidade Estadual de Campinas, São Paulo, Brazil

    Rita Xavier & Leandro N. de Castro

  2. U.A. Whitaker College of Engineering, Florida Gulf Coast University, Fort Myers, USA

    John Peller & Leandro N. de Castro

Authors
  1. Rita Xavier
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  2. John Peller
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  3. Leandro N. de Castro
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Corresponding authors

Correspondence to Rita Xavier , John Peller or Leandro N. de Castro .

Editor information

Editors and Affiliations

  1. Vellore Institute of Technology University, Vellore, Tamil Nadu, India

    Ravikumar Chinthaginjala

  2. Kielce University of Technology, Kielce, Poland

    Pawel Sitek

  3. Department of Computer Science, Imam Abdulrahman Bin Faisal University (KSA), Dammam, Saudi Arabia

    Nasro Min-Allah

  4. Osaka Institute of Technology, Osaka, Japan

    Kenji Matsui

  5. University Rey Juan Carlos, Madrid, Spain

    Sascha Ossowski

  6. Biotechnology, Intelligent Systems and Educational Technology (BISITE) Research Group, University of Salamanca, Salamanca, Spain

    Sara Rodríguez

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The authors have no competing interests to declare that are relevant to the content of this article.

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Xavier, R., Peller, J., de Castro, L.N. (2025). TRUNC: A Transfer Learning Unsupervised Network for Data Clustering. In: Chinthaginjala, R., Sitek, P., Min-Allah, N., Matsui, K., Ossowski, S., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 21st International Conference. DCAI 2024. Lecture Notes in Networks and Systems, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-031-82073-1_17

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