{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T23:24:10Z","timestamp":1775085850242,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":8,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811557873","type":"print"},{"value":"9789811557880","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T00:00:00Z","timestamp":1599609600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T00:00:00Z","timestamp":1599609600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-15-5788-0_24","type":"book-chapter","created":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T08:02:45Z","timestamp":1599552165000},"page":"255-264","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Investigation into the Efficacy of Various Machine Learning Techniques for Mitigation in Credit Card Fraud Detection"],"prefix":"10.1007","author":[{"given":"S. R.","family":"Lenka","sequence":"first","affiliation":[]},{"given":"M.","family":"Pant","sequence":"additional","affiliation":[]},{"given":"R. K.","family":"Barik","sequence":"additional","affiliation":[]},{"given":"S. S.","family":"Patra","sequence":"additional","affiliation":[]},{"given":"H.","family":"Dubey","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,9]]},"reference":[{"issue":"4","key":"24_CR1","doi-asserted-by":"publisher","first-page":"1721","DOI":"10.1016\/j.eswa.2007.08.093","volume":"35","author":"JT Quah","year":"2008","unstructured":"Quah, J.T., Sriganesh, M.: Real-time credit card fraud detection using computational intelligence. Expert Syst. Appl. 35(4), 1721\u20131732 (2008)","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"24_CR2","doi-asserted-by":"publisher","first-page":"80","DOI":"10.14445\/22315381\/IJETT-V62P214","volume":"62","author":"SR Lenka","year":"2018","unstructured":"Lenka, S.R., Ratha, B.K., Nayak, B.: A review on novel approach to handle imbalanced credit card transactions. Int. J. Eng. Trends Technol. (IJETT) 62(2), 80\u201395 (2018)","journal-title":"Int. J. Eng. Trends Technol. (IJETT)"},{"issue":"2","key":"24_CR3","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1016\/j.asoc.2009.08.003","volume":"10","author":"Chih-Fong Tsai","year":"2010","unstructured":"Tsai, Chih-Fong, Chen, Ming-Lun: Credit rating by hybrid machine learning techniques. Appl. Soft Comput. 10(2), 374\u2013380 (2010)","journal-title":"Appl. Soft Comput."},{"key":"24_CR4","doi-asserted-by":"publisher","first-page":"93010","DOI":"10.1109\/ACCESS.2019.2927266","volume":"7","author":"S Makki","year":"2019","unstructured":"Makki, S., Assaghir, Z., Taher, Y., Haque, R., Hacid, M.S., Zeineddine, H.: An experimental study with imbalanced classification approaches for credit card fraud detection. IEEE Access 7, 93010\u201393022 (2019)","journal-title":"IEEE Access"},{"key":"24_CR5","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1016\/j.neucom.2014.01.027","volume":"138","author":"DS Nascimento","year":"2014","unstructured":"Nascimento, D.S., Coelho, A.L., Canuto, A.M.: Integrating complementary techniques for promoting diversity in classifier ensembles: a systematic study. Neurocomputing. 138, 347\u2013357 (2014)","journal-title":"Neurocomputing."},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: Xgboost: a scalable tree boosting system. In: Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining. ACM (2016)","DOI":"10.1145\/2939672.2939785"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Awoyemi, J.O., Adetunmbi, A.O. and Oluwadare, S.A.: Credit card fraud detection using machine learning techniques: a comparative analysis. In: 2017 International Conference on Computing Networking and Informatics (ICCNI). IEEE (2017)","DOI":"10.1109\/ICCNI.2017.8123782"},{"issue":"1","key":"24_CR8","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.ejor.2015.05.030","volume":"247","author":"S Lessmann","year":"2015","unstructured":"Lessmann, S., et al.: Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research. Eur. J. Oper. Res. 247(1), 124\u2013136 (2015)","journal-title":"Eur. J. Oper. Res."}],"container-title":["Advances in Intelligent Systems and Computing","Evolution in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-5788-0_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T08:05:40Z","timestamp":1599552340000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-5788-0_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,9]]},"ISBN":["9789811557873","9789811557880"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-5788-0_24","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,9]]},"assertion":[{"value":"9 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}