{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T08:00:55Z","timestamp":1761897655066,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030932466"},{"type":"electronic","value":"9783030932473"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-93247-3_22","type":"book-chapter","created":{"date-parts":[[2021,12,30]],"date-time":"2021-12-30T00:03:20Z","timestamp":1640822600000},"page":"217-226","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Feature Engineering Based Credit Card Fraud Detection for Risk Minimization in E-Commerce"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4185-382X","authenticated-orcid":false,"given":"Md. Moinul","family":"Islam","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rony Chowdhury","family":"Ripan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saralya","family":"Roy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fazle","family":"Rahat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,1]]},"reference":[{"key":"22_CR1","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00979-3","volume-title":"Intelligent Computing & Optimization","year":"2019","unstructured":"Vasant, P., Zelinka, I., Weber, G.-W. (eds.): ICO 2018. AISC, vol. 866. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-00979-3"},{"key":"22_CR2","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33585-4","volume-title":"Intelligent Computing and Optimization","year":"2020","unstructured":"Vasant, P., Zelinka, I., Weber, G.-W. (eds.): ICO 2019. AISC, vol. 1072. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-33585-4"},{"key":"22_CR3","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68154-8","volume-title":"Intelligent Computing and Optimization","year":"2021","unstructured":"Vasant, P., Zelinka, I., Weber, G.-W. (eds.): ICO 2020. AISC, vol. 1324. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-68154-8"},{"issue":"3","key":"22_CR4","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","volume":"46","author":"NS Altman","year":"1992","unstructured":"Altman, N.S.: An introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46(3), 175\u2013185 (1992)","journal-title":"Am. Stat."},{"key":"22_CR5","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.eswa.2015.12.030","volume":"51","author":"AC Bahnsen","year":"2016","unstructured":"Bahnsen, A.C., Aouada, D., Stojanovic, A., Ottersten, B.: Feature engineering strategies for credit card fraud detection. Expert Syst. Appl. 51, 134\u2013142 (2016)","journal-title":"Expert Syst. Appl."},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Bahnsen, A.C., Stojanovic, A., Aouada, D., Ottersten, B.: Improving credit card fraud detection with calibrated probabilities. In: Proceedings of the 2014 SIAM International Conference on Data Mining, pp. 677\u2013685. SIAM (2014)","DOI":"10.1137\/1.9781611973440.78"},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Dubey, S.C., Mundhe, K.S., Kadam, A.A.: Credit card fraud detection using artificial neural network and backpropagation. In: 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 268\u2013273. IEEE (2020)","DOI":"10.1109\/ICICCS48265.2020.9120957"},{"key":"22_CR8","unstructured":"Gaikwad, J.R., Deshmane, A.B., Somavanshi, H.V., Patil, S.V., Badgujar, R.A.: Credit card fraud detection using decision tree induction algorithm. Int. J. Innov. Tech. Explori. Eng. (IJITEE) 4(6), 66 (2014)"},{"key":"22_CR9","doi-asserted-by":"crossref","unstructured":"Ho, T.K.: Random decision forests. In: Proceedings of 3rd International Conference on Document Analysis and Recognition, vol. 1, pp. 278\u2013282. IEEE (1995)","DOI":"10.1109\/ICDAR.1995.598994"},{"key":"22_CR10","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1016\/j.eswa.2018.01.037","volume":"100","author":"J Jurgovsky","year":"2018","unstructured":"Jurgovsky, J., et al.: Sequence classification for credit-card fraud detection. Expert Syst. Appl. 100, 234\u2013245 (2018)","journal-title":"Expert Syst. Appl."},{"key":"22_CR11","unstructured":"Li, C.: A gentle introduction to gradient boosting (2016). http:\/\/www.ccs.neu.edu\/home\/vip\/teach\/MLcourse\/4_boosting\/slides\/gradient_boosting.pdf"},{"key":"22_CR12","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/j.future.2019.08.029","volume":"102","author":"Y Lucas","year":"2020","unstructured":"Lucas, Y., et al.: Towards automated feature engineering for credit card fraud detection using multi-perspective HMMS. Future Gener. Comput. Syst. 102, 393\u2013402 (2020)","journal-title":"Future Gener. Comput. Syst."},{"key":"22_CR13","doi-asserted-by":"crossref","unstructured":"Marcano-Cede\u00f1o, A., Quintanilla-Dom\u00ednguez, J., Cortina-Januchs, M., Andina, D.: Feature selection using sequential forward selection and classification applying artificial metaplasticity neural network. In: IECON 2010\u201336th Annual Conference on IEEE Industrial Electronics Society, pp. 2845\u20132850. IEEE (2010)","DOI":"10.1109\/IECON.2010.5675075"},{"key":"22_CR14","doi-asserted-by":"crossref","unstructured":"Paper, D.: Scikit-Learn Classifier Tuning from Complex Training Sets, pp. 165\u2013188. Apress, Berkeley (2020)","DOI":"10.1007\/978-1-4842-5373-1_6"},{"key":"22_CR15","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.engappai.2018.03.011","volume":"72","author":"AG de S\u00e1","year":"2018","unstructured":"de S\u00e1, A.G., Pereira, A.C., Pappa, G.L.: A customized classification algorithm for credit card fraud detection. Eng. Appl. Artif. Intell. 72, 21\u201329 (2018)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"3","key":"22_CR16","first-page":"192","volume":"1","author":"G Singh","year":"2012","unstructured":"Singh, G., Gupta, R., Rastogi, A., Chandel, M.D., Ahmad, R.: A machine learning approach for detection of fraud based on SVM. Int. J. Sci. Eng. Technol. 1(3), 192\u2013196 (2012)","journal-title":"Int. J. Sci. Eng. Technol."},{"key":"22_CR17","doi-asserted-by":"publisher","first-page":"25579","DOI":"10.1109\/ACCESS.2020.2971354","volume":"8","author":"AA Taha","year":"2020","unstructured":"Taha, A.A., Malebary, S.J.: An intelligent approach to credit card fraud detection using an optimized light gradient boosting machine. IEEE Access 8, 25579\u201325587 (2020)","journal-title":"IEEE Access"},{"issue":"5","key":"22_CR18","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1001\/jama.2016.7653","volume":"316","author":"J Tolles","year":"2016","unstructured":"Tolles, J., Meurer, W.J.: Logistic regression: relating patient characteristics to outcomes. JAMA 316(5), 533\u2013534 (2016)","journal-title":"JAMA"},{"key":"22_CR19","unstructured":"ULB, M.L.G.: Credit card fraud detection (2018). https:\/\/www.kaggle.com\/mlg-ulb\/creditcardfraud"},{"issue":"5","key":"22_CR20","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/72.788640","volume":"10","author":"VN Vapnik","year":"1999","unstructured":"Vapnik, V.N.: An overview of statistical learning theory. IEEE Trans. Neural Netw. 10(5), 988\u2013999 (1999)","journal-title":"IEEE Trans. Neural Netw."},{"key":"22_CR21","doi-asserted-by":"crossref","unstructured":"Xuan, S., Liu, G., Li, Z., Zheng, L., Wang, S., Jiang, C.: Random forest for credit card fraud detection. In: 2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC), pp. 1\u20136. IEEE (2018)","DOI":"10.1109\/ICNSC.2018.8361343"},{"key":"22_CR22","unstructured":"Yee, O.S., Sagadevan, S., Malim, N.H.A.H.: Credit card fraud detection using machine learning as data mining technique. J. Telecommun. Electron. Comput. Eng. (JTEC) 10(1\u20134), 23\u201327 (2018)"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Computing & Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-93247-3_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T10:20:13Z","timestamp":1726395613000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-93247-3_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030932466","9783030932473"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-93247-3_22","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing & Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hua Hin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ico2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icico.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}