dc.contributor.author | Taşdemir, K. | |
dc.date.accessioned | 2021-01-25T20:51:49Z | |
dc.date.available | 2021-01-25T20:51:49Z | |
dc.date.issued | 2009 | |
dc.identifier | 10.1109/SIU.2009.5136521 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350335692&doi=10.1109%2fSIU.2009.5136521&partnerID=40&md5=40a096936a6001cfe2e2454527ba4992 | |
dc.identifier.uri | https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/10706 | |
dc.description.abstract | A powerful method in analysis of large data sets where there are many natural clusters with varying statistics such as different sizes, shapes, density distribution, is the use of self-organizing maps (SOMs) [1]. However, further processing tools, such as | |
dc.language.iso | English | |
dc.publisher | 2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 | |
dc.title | Automated clustering of large data sets based on a topology representing graph [Büyük veri kümelerinin topoloji betimleyen çizgeye dayali otomatik gruplandirmasi] | |
dc.type | Conference Paper | |
dc.relation.firstpage | 816 | |
dc.relation.lastpage | 819 | |
dc.description.affiliations | Bilgisayar Mühendisliǧi Bölümü, Yaşar Üniversitesi, Turkey | |