Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/34120
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dc.contributor.authorKumara, Soundar R.-
dc.date.accessioned2023-09-28T07:40:58Z-
dc.date.available2023-09-28T07:40:58Z-
dc.date.issued2014-07-
dc.identifier.citationÇavdur, F. ve Kumara, S. R. (2014). "Network mining: Applications to business data". Information Systems Frontiers, 16(3), 473-490.en_US
dc.identifier.issn1387-3326-
dc.identifier.issn1572-9419-
dc.identifier.urihttps://doi.org/10.1007/s10796-012-9355-z-
dc.identifier.urihttps://link.springer.com/article/10.1007/s10796-012-9355-z-
dc.identifier.urihttp://hdl.handle.net/11452/34120-
dc.description.abstractThis research addresses the problem of analyzing the temporal dynamics of business organizations. In particular, we concentrate on inferring the related businesses, i.e., are there groups of companies that are highly correlated through some measurement (metric)? We argue that business relationships derived from general literature (i.e., newspaper articles, news items etc.) may help us create a network of related companies (business networks). On the other hand, relative movement of stock prices can give us an indication of related companies (asset graphs). We also expect to see some relationships between these two kinds of networks. We adapt the asset graph construction approach from the literature for our asset graph implementations, and then, define our methodology for business network construction. Finally, an introduction to the exploration of some relationships between the asset graphs and business networks is presented.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlgorithmsen_US
dc.subjectStock marketen_US
dc.subjectBusiness systemsen_US
dc.subjectNetworksen_US
dc.subjectFinancial systemsen_US
dc.subjectNetwork miningen_US
dc.subjectAlgorithmsen_US
dc.subjectNetworks (circuits)en_US
dc.subjectFinanceen_US
dc.subjectBusiness networksen_US
dc.subjectBusiness organizationsen_US
dc.subjectHighly-correlateden_US
dc.subjectBusiness relationshipsen_US
dc.subjectGraph constructionen_US
dc.subjectBusiness systemsen_US
dc.subjectFinancial systemen_US
dc.subjectIndustryen_US
dc.subjectComputer Scienceen_US
dc.subjectDynamic asset treesen_US
dc.subjectFood websen_US
dc.subjectFinancial networksen_US
dc.subjectMarketsen_US
dc.subjectGraphsen_US
dc.titleNetwork mining: Applications to business dataen_US
dc.typeArticleen_US
dc.identifier.wos000338280900010tr_TR
dc.identifier.scopus2-s2.0-84903521253tr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.tr_TR
dc.contributor.orcid0000-0001-8054-5606tr_TR
dc.identifier.startpage473tr_TR
dc.identifier.endpage490tr_TR
dc.identifier.volume16tr_TR
dc.identifier.issue3tr_TR
dc.relation.journalInformation Systems Frontiersen_US
dc.contributor.buuauthorÇavdur, Fatih-
dc.contributor.researcheridAAG-9471-2021tr_TR
dc.relation.collaborationYurt dışıtr_TR
dc.subject.wosComputer Science, information systemsen_US
dc.subject.wosComputer Science, theory & methodsen_US
dc.indexed.wosSCIEen_US
dc.indexed.scopusScopusen_US
dc.wos.quartileQ2en_US
dc.contributor.scopusid8419687000tr_TR
dc.subject.scopusStock Market; Volatility Clustering; Time Series Analysisen_US
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