A self-supervised seed-driven approach to topic modelling and clustering

dc.contributor.author	Bahrainian, Seyed Ali
dc.date.accessioned	2026-01-09T08:15:46Z
dc.date.available	2026-01-09T08:15:46Z
dc.date.issued	2025
dc.identifier.issn	0925-9902
dc.identifier.uri	http://hdl.handle.net/10900/173824
dc.language.iso	en	en
dc.publisher	Dordrecht : Springer	de_DE
dc.relation.uri	http://dx.doi.org/10.1007/s10844-024-00891-8
dc.subject.ddc	004	de_DE
dc.title	A self-supervised seed-driven approach to topic modelling and clustering	de_DE
dc.type	Article	de_DE
utue.quellen.id	20250630000000_02630
utue.publikation.seiten	333-353	de_DE
utue.personen.roh	Ravenda, Federico
utue.personen.roh	Bahrainian, Seyed Ali
utue.personen.roh	Raballo, Andrea
utue.personen.roh	Mira, Antonietta
utue.personen.roh	Crestani, Fabio
dcterms.isPartOf.ZSTitelID	Journal of Intelligent Information Systems	de_DE
dcterms.isPartOf.ZS-Issue	1	de_DE
dcterms.isPartOf.ZS-Volume	63	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät