Ontology-Based Credit Card Fraud Detection

Using graphs as to extracting and presenting data has a wide range of applications. Such applications may appear in detecting semantic and structural patters and exploiting graphs toward such applications have steadily been growing. In this paper we are going to display one of the most perilous abnormalities in credit cards industry on such concept basis. With advancing technology in field of banking, the rate of use of credit cards has remarkably been escalated. Correspondingly frauds frequency have increased in this area which to surmount such anomalies we model them by means of graphs. Of the prominent advantage of proposed approach is drop of system overload rate during running computations in order to detecting frauds and consequently acceleration of detection speed.