Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/1312
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dc.creatorDobrota, Marina
dc.creatorBulajić, Milica
dc.creatorRadojičić, Zoran
dc.date.accessioned2023-05-12T10:49:53Z-
dc.date.available2023-05-12T10:49:53Z-
dc.date.issued2014
dc.identifier.urihttps://rfos.fon.bg.ac.rs/handle/123456789/1312-
dc.description.abstractData mining is a powerful technology with great potential to help companies focus on the most important information in their data warehouses (Fayyad et al., 1996; Xu and Zhang, 2005). Data mining tools can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions (Sharma et al., 2008). They scan databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Technologies that have been developed in the area of data mining and knowledge discovery in databases became necessary because the traditional analysis of data has been insufficient for a very long time (Frawley et al., 1991).en
dc.publisherPalgrave Macmillan
dc.rightsrestrictedAccess
dc.sourceInnovative Management and Firm Performance: An Interdisciplinary Approach and Cases
dc.titleData mining models for prediction of customers’ satisfaction: The CART analysisen
dc.typebookPart
dc.rights.licenseARR
dc.citation.epage421
dc.citation.other: 401-421
dc.citation.spage401
dc.identifier.doi10.1057/9781137402226_21
dc.identifier.rcubconv_3497
dc.identifier.scopus2-s2.0-85015888667
dc.type.versionpublishedVersion
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypebookPart-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Collections:Radovi istraživača / Researchers’ publications
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