<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/17FF1E01-05EC-4E32-A6B6-0B6A87142E2D"><efrbr-work:titleOfTheWork>CCAS: an intelligent decision support system for credit card assessment</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/17FF1E01-05EC-4E32-A6B6-0B6A87142E2D"><efrbr-expression:titleOfTheExpression>CCAS: an intelligent decision support system for credit card assessment</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Peer-Reviewed Journal Publication
            Δημοσίευση σε Περιοδικό με Κριτές
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-11-03</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2002</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>During the last two decades credit cards have became one of the main ways for accomplishing financial transactions. The number of credit card owners have increased rapidly. Unfortunately, at the same time the cases where the owners cannot fulfil their obligations to the banks have also been increased. This fact forced credit institutions and banks to search for methodologies that will allow them to accurately evaluate the credibility of each credit card applicant. Multi-criteria decision aid methods as well as machine learning algorithms can be used to accomplish this task. The present paper proposes a new intelligent decision support system for credit card evaluation, based on a machine-learning algorithm, namely the Composite Rule Induction System and the Rough Sets. The major advantage of the algorithm and the system is the incorporation of qualitative variables, which have an essential role in credit card evaluation. The system is applied on a real case study concerning credit card evaluation by a leading Greek commercial bank and the obtained results are compared to the results of multi-criteria decision aid methods as well as other machine learning algorithms.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="journal name">Journal of Multi-Criteria Decision Analysis</efrbr-expression:note><efrbr-expression:note type="journal volume">4-5</efrbr-expression:note><efrbr-expression:note type="journal number">11</efrbr-expression:note><efrbr-expression:note type="page range">213-235</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~nmatsatsinis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Matsatsinis Nikolaos
            Ματσατσινης Νικολαος
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-corporateBody:corporateBody identifier="http://www.wiley.com/"><efrbr-corporateBody:nameOfTheCorporateBody vocabulary="S/R:PUBLISHERS">
            John Wiley and Sons
         </efrbr-corporateBody:nameOfTheCorporateBody></efrbr-corporateBody:corporateBody><efrbr-concept:concept identifier="http://id.loc.gov/authorities/subjects/sh85033865"><efrbr-concept:termForTheConcept>
            Cards, Charge
            Cards, Credit
            Charge cards
            credit cards
            cards charge
            cards credit
            charge cards
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