{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T01:02:40Z","timestamp":1770339760314,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671521","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:55:12Z","timestamp":1724561712000},"page":"5959-5968","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3928-4235","authenticated-orcid":false,"given":"Chengyao","family":"Wen","sequence":"first","affiliation":[{"name":"Ant Group, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8329-7192","authenticated-orcid":false,"given":"Yin","family":"Lou","sequence":"additional","affiliation":[{"name":"Ant Group, Sunnyvale, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"2024. Github repo. https:\/\/github.com\/ChengyaoWen\/Pareto-Optimal-Rule-Subset-Selection"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"R. Agrawal T. Imielinski and A. Swami. 1993. Mining association rules between sets of items in large databases. In SIGMOD.","DOI":"10.1145\/170035.170072"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00009"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2006.08.008"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_2_6_1","unstructured":"L. Breiman J.H. Friedman C.J. Stone and R.A. Olshen. 1984. Classification and regression trees. Chapman and Hall\/CRC."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"W. Chen H. Ishibuchi and K. Shang. 2021. Clustering-based subset selection in evolutionary multiobjective optimization. In SMC.","DOI":"10.1109\/SMC52423.2021.9658582"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2021.3103386"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1022641700528"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"crossref","unstructured":"W.W. Cohen. 1995. Fast effective rule induction. In ICML.","DOI":"10.1016\/B978-1-55860-377-6.50023-2"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"key":"e_1_3_2_2_12_1","unstructured":"A.P. Guerreiro C.M. Fonseca and L. Paquete. 2020. The hypervolume indicator: Problems and algorithms. arXiv preprint arXiv:2005.00515 (2020)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"crossref","unstructured":"H. Lakkaraju S.H. Bach and J. Leskovec. 2016. Interpretable decision sets: A joint framework for description and prediction. In KDD.","DOI":"10.1145\/2939672.2939874"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2792984"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3154815"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"M. Li L. Yu Y.-L. Zhang X Huang Q. Shi Q. Cui X. Yang L. Li W. Zhu Y. Fang and J. Zhou. 2022. An adaptive framework for confidence-constraint rule set learning algorithm in large dataset. In CIKM.","DOI":"10.1145\/3511808.3557088"},{"key":"e_1_3_2_2_17_1","unstructured":"C. Molnar. 2020. Interpretable machine learning. Lulu. com."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mcm.2010.12.044"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.14778\/3611540.3611621"},{"key":"e_1_3_2_2_20_1","volume-title":"Programs for machine learning","author":"Quinlan J.R.","unstructured":"J.R. Quinlan. 1993. C4.5: Programs for machine learning. Morgan Kaufmann Publishers."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"K. Shang T. Shu H. Ishibuchi Y. Nan and L.M. Pang. 2022. Benchmarking subset selection from large candidate solution sets in evolutionary multi-objective optimization. arXiv preprint arXiv:2201.06700 (2022).","DOI":"10.1016\/j.ins.2022.11.155"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2751071"},{"key":"e_1_3_2_2_23_1","unstructured":"C.J. Van Rijsbergen. 1979. Information retrieval. Butterworth-Heinemann."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"crossref","unstructured":"G. Zhang and A. Gionis. 2020. Diverse rule sets. In KDD.","DOI":"10.1145\/3394486.3403204"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2007.892759"},{"key":"e_1_3_2_2_26_1","unstructured":"E. Zitzler. 1999. Evolutionary algorithms for multiobjective optimization: Methods and applications. Ph. D. Dissertation. ETH Zurich Switzerland."},{"key":"e_1_3_2_2_27_1","unstructured":"E. Zitzler M. Laumanns and L. Thiele. 2001. SPEA2: Improving the strength Pareto evolutionary algorithm. Technical Report. ETHZ Z\u00fcrich Switzerland."}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671521","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671521","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:19Z","timestamp":1750291459000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671521"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":27,"alternative-id":["10.1145\/3637528.3671521","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671521","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}