{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,3]],"date-time":"2025-06-03T22:04:24Z","timestamp":1748988264190,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031368042"},{"type":"electronic","value":"9783031368059"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-36805-9_35","type":"book-chapter","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T23:03:04Z","timestamp":1688079784000},"page":"535-549","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Bee Colony Algorithm for\u00a0Feature Selection in\u00a0Fraud Detection Process"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2917-9182","authenticated-orcid":false,"given":"Gabriel Covello","family":"Furlanetto","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4176-566X","authenticated-orcid":false,"given":"Vitoria Zanon","family":"Gomes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1123-9784","authenticated-orcid":false,"given":"Fabricio Aparecido","family":"Breve","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,30]]},"reference":[{"key":"35_CR1","doi-asserted-by":"crossref","unstructured":"Agrawal, V., Chandra, S.: Feature selection using artificial bee colony algorithm for medical image classification. In: 2015 Eighth International Conference on Contemporary Computing (IC3), pp. 171\u2013176. IEEE (2015)","DOI":"10.1109\/IC3.2015.7346674"},{"issue":"1\u20132","key":"35_CR2","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1504\/IJAIP.2013.054681","volume":"5","author":"JC Bansal","year":"2013","unstructured":"Bansal, J.C., Sharma, H., Jadon, S.S.: Artificial bee colony algorithm: a survey. Int. J. Adv. Intell. Paradigms 5(1\u20132), 123\u2013159 (2013)","journal-title":"Int. J. Adv. Intell. Paradigms"},{"key":"35_CR3","doi-asserted-by":"publisher","unstructured":"Chen, X.w., Jeong, J.C.: Enhanced recursive feature elimination. In: Sixth International Conference on Machine Learning and Applications (ICMLA 2007), pp. 429\u2013435 (2007). https:\/\/doi.org\/10.1109\/ICMLA.2007.35","DOI":"10.1109\/ICMLA.2007.35"},{"issue":"2","key":"35_CR4","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1007\/s00500-019-03958-9","volume":"24","author":"SM Darwish","year":"2020","unstructured":"Darwish, S.M.: An intelligent credit card fraud detection approach based on semantic fusion of two classifiers. Soft. Comput. 24(2), 1243\u20131253 (2020)","journal-title":"Soft. Comput."},{"issue":"2","key":"35_CR5","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1162\/106454699568728","volume":"5","author":"M Dorigo","year":"1999","unstructured":"Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant algorithms for discrete optimization. Artif. Life 5(2), 137\u2013172 (1999)","journal-title":"Artif. Life"},{"key":"35_CR6","doi-asserted-by":"crossref","unstructured":"Eberhart, R., Kennedy, J.: Particle swarm optimization. In: Proceedings of the IEEE International Conference On Neural Networks. vol. 4, pp. 1942\u20131948. Citeseer (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"key":"35_CR7","doi-asserted-by":"crossref","unstructured":"El Aboudi, N., Benhlima, L.: Review on wrapper feature selection approaches. In: 2016 International Conference on Engineering & MIS (ICEMIS), pp. 1\u20135. IEEE (2016)","DOI":"10.1109\/ICEMIS.2016.7745366"},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Annals of statistics, pp. 1189\u20131232 (2001)","DOI":"10.1214\/aos\/1013203451"},{"key":"35_CR9","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.asoc.2015.07.023","volume":"36","author":"E Hancer","year":"2015","unstructured":"Hancer, E., Xue, B., Karaboga, D., Zhang, M.: A binary abc algorithm based on advanced similarity scheme for feature selection. Appl. Soft Comput. 36, 334\u2013348 (2015)","journal-title":"Appl. Soft Comput."},{"key":"35_CR10","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":"35_CR11","unstructured":"Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Tech. rep., Technical report-tr06, Erciyes university, engineering faculty, computer engineering department (2005)"},{"issue":"1","key":"35_CR12","first-page":"108","volume":"214","author":"D Karaboga","year":"2009","unstructured":"Karaboga, D., Akay, B.: A comparative study of artificial bee colony algorithm. Appl. Math. Comput. 214(1), 108\u2013132 (2009)","journal-title":"Appl. Math. Comput."},{"key":"35_CR13","volume-title":"Logistic Regression","author":"DG Kleinbaum","year":"2002","unstructured":"Kleinbaum, D.G., Dietz, K., Gail, M., Klein, M., Klein, M.: Logistic Regression. Springer, New York (2002)"},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Lanzi, P.L.: Fast feature selection with genetic algorithms: a filter approach. In: Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC\u201997), pp. 537\u2013540. IEEE (1997)","DOI":"10.1109\/ICEC.1997.592369"},{"key":"35_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1007\/978-3-642-04070-2_116","volume-title":"Emerging Intelligent Computing Technology and Applications","author":"O Liu","year":"2009","unstructured":"Liu, O., Ma, J., Poon, P.-L., Zhang, J.: On an ant colony-based approach for business fraud detection. In: Huang, D.-S., Jo, K.-H., Lee, H.-H., Kang, H.-J., Bevilacqua, V. (eds.) ICIC 2009. LNCS, vol. 5754, pp. 1104\u20131111. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-04070-2_116"},{"issue":"3","key":"35_CR16","first-page":"432","volume":"9","author":"S Palanisamy","year":"2012","unstructured":"Palanisamy, S., Kanmani, S.: Artificial bee colony approach for optimizing feature selection. Int. J. Comput. Sci. Issues (IJCSI) 9(3), 432 (2012)","journal-title":"Int. J. Comput. Sci. Issues (IJCSI)"},{"key":"35_CR17","unstructured":"Pavithra, T., Thangadurai, D.K.: Fraud detection of credit cards using abc methodology based on svm algorithm (2019)"},{"key":"35_CR18","unstructured":"Yang, Y., Pedersen, J.O.: A comparative study on feature selection in text categorization. In: Icml. vol. 97, pp. 412\u2013420. Nashville, TN, USA (1997)"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-36805-9_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T10:31:48Z","timestamp":1729679508000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-36805-9_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031368042","9783031368059"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-36805-9_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Custom based on Cyberchair 4","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"283","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"PHD Showcase Papers: 6(for main conf) \/ For ICCSA 2023 Workshops 876 subm sent, 350 full papers and 29 short papers accepted, additional PHD Showcase Papers: 2","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}