Painter Profile Clustering Using NLP Features

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dc.contributor.authorIlba, N. Yagmur
dc.contributor.authorYildirim, U. Mahir
dc.contributor.authorSen, Doruk
dc.date.accessioned2026-04-04T18:48:30Z
dc.date.available2026-04-04T18:48:30Z
dc.date.issued2024
dc.description9th International Conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2024 -- 28 April 2024 through 29 April 2024 -- Angers -- 199583
dc.description.abstractThis study introduces a practice for clustering painter profiles using features obtained from natural language processing (NLP) techniques. The investigation of similarities among painters plays an essential function in art history. While most existing research generally focuses on the visual comparison of the artists' work, more studies should examine the textual content available for artists. As the volume of online textual information grows, the frequency of discussions about artists and their creations has gained importance, underscoring the connection between social visibility through digital discourse and an artist's recognition. This research provides a method for investigating Wikipedia profiles of painters using NLP attributes. Among unsupervised machine learning algorithms, the K-means is adopted to group the painters using the driven attributes from the content details of their profile pages. The clustering results are evaluated through a benchmark painter list and a qualitative review. The model findings reveal that the suggested approach effectively clusters the presented benchmark painter profiles, highlighting the potential of textual data analysis on painter profile similarities. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.
dc.description.sponsorshipIstanbul Bilgi University Scientific Research Projects Fund, (AK85098)
dc.description.sponsorshipInstitute for Systems and Technologies of Information, Control and Communication (INSTICC)
dc.identifier.doi10.5220/0012623700003708
dc.identifier.endpage98
dc.identifier.isbn978-989758698-9
dc.identifier.issn2184-5034
dc.identifier.scopus2-s2.0-85194175856
dc.identifier.scopusqualityQ4
dc.identifier.startpage91
dc.identifier.urihttps://doi.org/10.5220/0012623700003708
dc.identifier.urihttps://hdl.handle.net/11411/10181
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherScience and Technology Publications, Lda
dc.relation.ispartofInternational Conference on Complexity, Future Information Systems and Risk, COMPLEXIS - Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20260402
dc.subjectClustering
dc.subjectNatural Language Processing
dc.subjectText Analysis
dc.subjectXai
dc.titlePainter Profile Clustering Using NLP Features
dc.typeConference Paper

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