{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:22:56Z","timestamp":1778883776231,"version":"3.51.4"},"reference-count":14,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2006,3]]},"abstract":"<jats:p> Recently, a new personalized model has been developed to prevent credit card fraud. This model is promising; however, there remains some problems. Existing approaches cannot identify well credit card frauds from few data with skewed distributions. This paper proposes to address the problem using a binary support vector system (BSVS). The proposed BSVS is based on the support vectors in the support vector machines (SVM) and the genetic algorithm (GA) is employed to select support vectors. To obtain a high true negative rate, self-organizing mapping (SOM) is first employed to estimate the distribution model of the input data. Then BSVS is used to best train the data according to the input data distribution to obtain a high detection rate. Experimental results show that the proposed BSVS is effective especially for predicting a high true negative rate. <\/jats:p>","DOI":"10.1142\/s0218001406004624","type":"journal-article","created":{"date-parts":[[2006,3,21]],"date-time":"2006-03-21T05:41:10Z","timestamp":1142919670000},"page":"227-239","source":"Crossref","is-referenced-by-count":58,"title":["A NEW BINARY SUPPORT VECTOR SYSTEM FOR INCREASING DETECTION RATE OF CREDIT CARD FRAUD"],"prefix":"10.1142","volume":"20","author":[{"given":"RONG-CHANG","family":"CHEN","sequence":"first","affiliation":[{"name":"Department of Logistics Engineering and Management, Taichung, Taiwan 404, R.O.C"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TUNG-SHOU","family":"CHEN","sequence":"additional","affiliation":[{"name":"Graduate School of Computer Science and Information Technology, Taichung, Taiwan 404, R.O.C"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"CHIH-CHIANG","family":"LIN","sequence":"additional","affiliation":[{"name":"Graduate School of Computer Science and Information Technology, Taichung, Taiwan 404, R.O.C"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,4,30]]},"reference":[{"key":"rf2","first-page":"262","author":"Brown M. P. S.","journal-title":"Proc. Natl. Acad. USA"},{"key":"rf3","first-page":"955","volume":"2","author":"Burges C. J. C.","journal-title":"Data Min. Knowl. Disco."},{"key":"rf4","first-page":"67","author":"Chan P. K.","journal-title":"IEEE Intell. Syst."},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-28651-6_119"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1007\/11427445_147"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2003.11.003"},{"key":"rf9","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(00)00099-4"},{"key":"rf10","volume-title":"Systematic Theory of Neural Networks for Pattern Recognition","author":"Huang D. S.","year":"1996"},{"key":"rf11","doi-asserted-by":"publisher","DOI":"10.1515\/JISYS.1999.9.1.1"},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001499000604"},{"key":"rf14","volume-title":"Machine Learning","author":"Mitchell T. M.","year":"1997"},{"key":"rf15","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/3163.001.0001","volume-title":"Fundamentals of Neural Network Modeling Neuro-psychology and Cognitive Neuroscience","author":"Parks R. W.","year":"1998"},{"key":"rf18","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2004.836938"},{"key":"rf19","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001406004624","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T13:00:42Z","timestamp":1565096442000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001406004624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,3]]},"references-count":14,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2012,4,30]]},"published-print":{"date-parts":[[2006,3]]}},"alternative-id":["10.1142\/S0218001406004624"],"URL":"https:\/\/doi.org\/10.1142\/s0218001406004624","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,3]]}}}