{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T22:14:37Z","timestamp":1784585677962,"version":"3.55.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206059"],"award-info":[{"award-number":["62206059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1936213"],"award-info":[{"award-number":["U1936213"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2022M710747"],"award-info":[{"award-number":["2022M710747"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chinese National Key Laboratory of Science and Technology on Information System Security"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1109\/tkde.2024.3487625","type":"journal-article","created":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T17:35:14Z","timestamp":1730223314000},"page":"116-129","source":"Crossref","is-referenced-by-count":2,"title":["CauseRuDi: Explaining Behavior Sequence Models by Causal Statistics Generation and Rule Distillation"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1481-8826","authenticated-orcid":false,"given":"Yao","family":"Zhang","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8575-5415","authenticated-orcid":false,"given":"Yun","family":"Xiong","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiheng","family":"Sun","sequence":"additional","affiliation":[{"name":"Tencent Weixin Group, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yucheng","family":"Jin","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Data Science, School of Computer Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caihua","family":"Shan","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3730-1897","authenticated-orcid":false,"given":"Tian","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Arizona State University, Tempe, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Song","sequence":"additional","affiliation":[{"name":"Tencent Weixin Group, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9573-0780","authenticated-orcid":false,"given":"Shengli","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Software and Microelectronics, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005589"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412161"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3409382"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6102"},{"key":"ref5","first-page":"30479","article-title":"Scalable rule-based representation learning for interpretable classification","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref6","first-page":"234:1","article-title":"Learning certifiably optimal rule lists for categorical data","volume":"18","author":"Angelino","year":"2017","journal-title":"J. Mach. Learn. Res."},{"key":"ref7","first-page":"3921","article-title":"Scalable Bayesian rule lists","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yang"},{"key":"ref8","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"Guyon","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"key":"ref10","first-page":"3146","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Ke"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2012.2186810"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2014.6932889"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0679-x"},{"key":"ref14","first-page":"1","article-title":"Categorical reparameterization with gumbel-softmax","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Jang"},{"key":"ref15","article-title":"Learning algorithms via neural logic networks","author":"Payani","year":"2019"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0190"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0123"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207410"},{"key":"ref19","article-title":"DIFER: Differentiable automated feature engineering","author":"Zhu","year":"2020"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA.2015.7344858"},{"key":"ref21","article-title":"One button machine for automating feature engineering in relational databases","author":"Lam","year":"2017"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1515\/jci-2017-0016"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1126\/science.aal3856"},{"key":"ref24","first-page":"804","article-title":"Kernel-based conditional independence test and application in causal discovery","volume-title":"Proc. 27th Conf. Uncertainty Artif. Intell.","author":"Zhang"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/11564089_7"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/e20050385"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2883537"},{"key":"ref28","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3278721.3278725"},{"key":"ref30","article-title":"Distilling knowledge from deep networks with applications to healthcare domain","author":"Che","year":"2015"},{"key":"ref31","article-title":"Distilling a neural network into a soft decision tree","author":"Frosst","year":"2017"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2018.00132"},{"key":"ref33","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lundberg"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1228"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/11871842_29"},{"key":"ref36","first-page":"75","article-title":"Comparing UCT versus CFR in simultaneous games","volume-title":"Proc. IJCAI Workshop Gen. Game Playing","author":"Schaeffer"},{"key":"ref37","first-page":"104","article-title":"Monte Carlo tree search for simultaneous move games: A case study in the game of tron","volume-title":"Proc. 25th Benelux Conf. Artif. Intell.","author":"Lanctot"},{"key":"ref38","volume-title":"Multiple Regression: A Primer","author":"Allison","year":"1999"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783367"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557441"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1214\/009053604000000067.MR2060166"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1214\/009053607000000505"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2019.01.016"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/69\/10786487\/10737680.pdf?arnumber=10737680","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T20:17:15Z","timestamp":1736972235000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10737680\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":44,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2024.3487625","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]}}}