Custom Glial Network Architectures for the Classification of Large Text Corpora: A Case Study of Complaint Analysis in the Polish State Railways
Custom Glial Network Architectures for the Classification of Large Text Corpora: A Case Study of Complaint Analysis in the Polish State Railways
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Authors
Nowak, Jakub
Krumholc, Tymoteusz
Milewski, Jakub
Maćkiewicz, Aneta
Stachowiak, Sylwia
Korytkowski, Marcin
Scherer, Rafał
Monograph
Artificial Intelligence and Soft Computing: 24th International Conference, ICAISC 2025, Zakopane, Poland, June 22–26, 2025, Proceedings, Part I
Monograph (alternative title)
Editor
Rutkowski, Leszek
Scherer, Rafał
Korytkowski, Marcin
Pedrycz, Witold
Tadeusiewicz, Ryszard
Zurada, Jacek M.
Date
2025-11-01
Place of publication
Publisher
Springer Nature
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Volume
1
Pages
170-181
ISSN
ISBN
978-3-032-03704-6
eISBN
Series
Lecture Notes in Computer Science
Series number
15948
ISSN of series
0302-9743
Access date
2025-10-31
Remarks
Abstract PL
Abstract EN
We employ a custom-designed convolutional-glial network architecture for the classification of large text corpora. The problem selected to demonstrate the high effectiveness of the proposed technique, was defined in collaboration with Poland’s largest railway operator. The task involves categorizing incoming reports (submitted by passengers, station staff, and railway line personnel) into appropriate departments based on their textual content. The input data consists of short texts containing complaints, inquiries, and remarks, which were transformed into vector representations using the BERT language model. A hybrid convolutional architecture was then applied, augmented with a glial-type control module that dynamically regulates the activation levels of CNN filters. This glial control layer, inspired by biological mechanisms, was trained alternately with the convolutional component, enabling better adaptation of information flow within the network. Experimental results confirm that this approach outperforms classic architectures in terms of classification accuracy, while also offering greater flexibility and development potential. The proposed solution can be effectively applied in customer service support systems and automated text analysis for public transportation.
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Conference edition name
Artificial Intelligence and Soft Computing 24th International Conference, ICAISC 2025, Zakopane, Poland, June 22–26, 2025, Proceedings, Part I Conference proceedings © 2026
Conference place
Zakopane
Start date
2025-06-22
Finish date
2025-06-26
Sustainable Development Goals
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Organisational Unit
Wydział Projektowania w Warszawie
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