Evaluating the semantic clustering power of LLMs on ERP support texts

Basit Öğe Kaydı
dc.contributor.authorCanlı, Hikmet
dc.date.accessioned2025-12-25T10:20:21Z
dc.date.available2025-12-25T10:20:21Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractIn this study, 6,076 IT request records obtained from the IT support software of a corporate company were analyzed in terms of clustering using text mining techniques. The aim is to improve process management by obtaining meaningful groups from unstructured text data. For text representation, the traditional TF-IDF method was used alongside deep learning-based BERT and GPT-2 models. The K-Means algorithm was applied to all three representations with different numbers of clusters; the performance of the clusters was evaluated using Silhouette and Davies-Bouldin scores. The results showed that GPT-2-based representations created more successful and discriminative clusters compared to classical methods. These findings highlight the potential of advanced language models in the automatic classification of corporate requests and the digitization of business processes.
dc.identifier.doi10.1109/IDAP68205.2025.11222140
dc.identifier.isbn9798331589905
dc.identifier.scopus2-s2.0-105025007129
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP68205.2025.11222140
dc.identifier.urihttps://hdl.handle.net/11501/2575
dc.indekslendigikaynakScopus
dc.institutionauthorCanlı, Hikmet
dc.institutionauthorid0000-0003-3394-7113
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof9th International Artificial Intelligence and Data Processing Symposium, IDAP 2025
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBERT
dc.subjectERP
dc.subjectGPT-2
dc.subjectLLMs
dc.subjectTF-IDF
dc.titleEvaluating the semantic clustering power of LLMs on ERP support texts
dc.typeConference Object

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Kapalı Erişim
İsim:
Tam Metin / Full Text
Boyut:
1.28 MB
Biçim:
Adobe Portable Document Format
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Kapalı Erişim
İsim:
license.txt
Boyut:
1.17 KB
Biçim:
Item-specific license agreed to upon submission
Açıklama:
İndir

Koleksiyon

Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu