{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:07:56Z","timestamp":1765544876232,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"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"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"DOI":"10.1145\/3511808.3557441","type":"proceedings-article","created":{"date-parts":[[2022,10,16]],"date-time":"2022-10-16T01:22:22Z","timestamp":1665883342000},"page":"2651-2660","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation"],"prefix":"10.1145","author":[{"given":"Yao","family":"Zhang","sequence":"first","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Yun","family":"Xiong","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Yiheng","family":"Sun","sequence":"additional","affiliation":[{"name":"Tencent Weixin Group, Shenzhen, China"}]},{"given":"Caihua","family":"Shan","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Shanghai, China"}]},{"given":"Tian","family":"Lu","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, China"}]},{"given":"Hui","family":"Song","sequence":"additional","affiliation":[{"name":"Tencent Weixin Group, Shenzhen, China"}]},{"given":"Yangyong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"volume-title":"Multiple regression: A primer","author":"Allison Paul D","key":"e_1_3_2_1_1_1","unstructured":"Paul D Allison . 1999. Multiple regression: A primer . Pine Forge Press . Paul D Allison. 1999. Multiple regression: A primer. Pine Forge Press."},{"key":"e_1_3_2_1_2_1","volume-title":"Learning certifiably optimal rule lists for categorical data. Journal of Machine Learning Research","author":"Angelino Elaine","year":"2017","unstructured":"Elaine Angelino , Nicholas Larus-Stone , Daniel Alabi , Margo Seltzer , and Cynthia Rudin . 2017. Learning certifiably optimal rule lists for categorical data. Journal of Machine Learning Research ( 2017 ). Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo Seltzer, and Cynthia Rudin. 2017. Learning certifiably optimal rule lists for categorical data. Journal of Machine Learning Research (2017)."},{"volume-title":"Classification and regression trees","author":"Breiman Leo","key":"e_1_3_2_1_3_1","unstructured":"Leo Breiman , Jerome H Friedman , Richard A Olshen , and Charles J Stone . 2017. Classification and regression trees . Routledge . Leo Breiman, Jerome H Friedman, Richard A Olshen, and Charles J Stone. 2017. Classification and regression trees. Routledge."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2012.2186810"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2883537"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/e20050385"},{"key":"e_1_3_2_1_7_1","volume-title":"Distilling knowledge from deep networks with applications to healthcare domain. arXiv preprint arXiv:1512.03542","author":"Che Zhengping","year":"2015","unstructured":"Zhengping Che , Sanjay Purushotham , Robinder Khemani , and Yan Liu . 2015. Distilling knowledge from deep networks with applications to healthcare domain. arXiv preprint arXiv:1512.03542 ( 2015 ). Zhengping Che, Sanjay Purushotham, Robinder Khemani, and Yan Liu. 2015. Distilling knowledge from deep networks with applications to healthcare domain. arXiv preprint arXiv:1512.03542 (2015)."},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Statistical comparisons of classifiers over multiple data sets","volume":"7","author":"Janez Demvs","year":"2006","unstructured":"Janez Demvs ar. 2006 . Statistical comparisons of classifiers over multiple data sets . Journal of Machine Learning Research , Vol. 7 (2006), 1 -- 30 . Janez Demvs ar. 2006. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, Vol. 7 (2006), 1--30.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053604000000067"},{"key":"e_1_3_2_1_10_1","volume-title":"Distilling a neural network into a soft decision tree. arXiv preprint arXiv:1711.09784","author":"Frosst Nicholas","year":"2017","unstructured":"Nicholas Frosst and Geoffrey Hinton . 2017. Distilling a neural network into a soft decision tree. arXiv preprint arXiv:1711.09784 ( 2017 ). Nicholas Frosst and Geoffrey Hinton. 2017. Distilling a neural network into a soft decision tree. arXiv preprint arXiv:1711.09784 (2017)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"key":"e_1_3_2_1_12_1","unstructured":"Geoffrey Hinton Oriol Vinyals Jeff Dean etal 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 Vol. 2 7 (2015).  Geoffrey Hinton Oriol Vinyals Jeff Dean et al. 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 Vol. 2 7 (2015)."},{"key":"e_1_3_2_1_13_1","volume-title":"Harnessing deep neural networks with logic rules. arXiv preprint arXiv:1603.06318","author":"Hu Zhiting","year":"2016","unstructured":"Zhiting Hu , Xuezhe Ma , Zhengzhong Liu , Eduard Hovy , and Eric Xing . 2016. Harnessing deep neural networks with logic rules. arXiv preprint arXiv:1603.06318 ( 2016 ). Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016. Harnessing deep neural networks with logic rules. arXiv preprint arXiv:1603.06318 (2016)."},{"key":"e_1_3_2_1_14_1","volume-title":"International Conference on Learning Representations.","author":"Jang Eric","year":"2017","unstructured":"Eric Jang , Shixiang Gu , and Ben Poole . 2017 . Categorical reparameterization with gumbel-softmax . In International Conference on Learning Representations. Eric Jang, Shixiang Gu, and Ben Poole. 2017. Categorical reparameterization with gumbel-softmax. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/DSAA.2015.7344858"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0123"},{"key":"e_1_3_2_1_17_1","volume-title":"Conference on Neural Information Processing Systems","volume":"30","author":"Ke Guolin","year":"2017","unstructured":"Guolin Ke , Qi Meng , Thomas Finley , Taifeng Wang , Wei Chen , Weidong Ma , Qiwei Ye , and Tie-Yan Liu . 2017 . Lightgbm: A highly efficient gradient boosting decision tree . In Conference on Neural Information Processing Systems , Vol. 30 . Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017. Lightgbm: A highly efficient gradient boosting decision tree. In Conference on Neural Information Processing Systems, Vol. 30."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0190"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/11871842_29"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783367"},{"key":"e_1_3_2_1_21_1","volume-title":"One button machine for automating feature engineering in relational databases. arXiv preprint arXiv:1706.00327","author":"Lam Hoang Thanh","year":"2017","unstructured":"Hoang Thanh Lam , Johann-Michael Thiebaut , Mathieu Sinn , Bei Chen , Tiep Mai , and Oznur Alkan . 2017. One button machine for automating feature engineering in relational databases. arXiv preprint arXiv:1706.00327 ( 2017 ). Hoang Thanh Lam, Johann-Michael Thiebaut, Mathieu Sinn, Bei Chen, Tiep Mai, and Oznur Alkan. 2017. One button machine for automating feature engineering in relational databases. arXiv preprint arXiv:1706.00327 (2017)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2018.00132"},{"key":"e_1_3_2_1_23_1","volume-title":"Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554","author":"Payani Ali","year":"2019","unstructured":"Ali Payani and Faramarz Fekri . 2019. Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554 ( 2019 ). Ali Payani and Faramarz Fekri. 2019. Learning algorithms via neural logic networks. arXiv preprint arXiv:1904.01554 (2019)."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207410"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3278721.3278725"},{"key":"e_1_3_2_1_26_1","volume-title":"Scalable Rule-Based Representation Learning for Interpretable Classification. In Conference on Neural Information Processing Systems","volume":"34","author":"Wang Zhuo","year":"2021","unstructured":"Zhuo Wang , Wei Zhang , Ning Liu , and Jianyong Wang . 2021 . Scalable Rule-Based Representation Learning for Interpretable Classification. In Conference on Neural Information Processing Systems , Vol. 34 . Zhuo Wang, Wei Zhang, Ning Liu, and Jianyong Wang. 2021. Scalable Rule-Based Representation Learning for Interpretable Classification. In Conference on Neural Information Processing Systems, Vol. 34."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6102"},{"key":"e_1_3_2_1_28_1","volume-title":"International Conference on Machine Learning. 3921--3930","author":"Yang Hongyu","year":"2017","unstructured":"Hongyu Yang , Cynthia Rudin , and Margo Seltzer . 2017 . Scalable Bayesian rule lists . In International Conference on Machine Learning. 3921--3930 . Hongyu Yang, Cynthia Rudin, and Margo Seltzer. 2017. Scalable Bayesian rule lists. In International Conference on Machine Learning. 3921--3930."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3409382"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005589"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412161"},{"key":"e_1_3_2_1_32_1","volume-title":"DIFER: Differentiable Automated Feature Engineering. arXiv preprint arXiv:2010.08784","author":"Zhu Guanghui","year":"2020","unstructured":"Guanghui Zhu , Zhuoer Xu , Xu Guo , Chunfeng Yuan , and Yihua Huang . 2020 . DIFER: Differentiable Automated Feature Engineering. arXiv preprint arXiv:2010.08784 (2020). Guanghui Zhu, Zhuoer Xu, Xu Guo, Chunfeng Yuan, and Yihua Huang. 2020. DIFER: Differentiable Automated Feature Engineering. arXiv preprint arXiv:2010.08784 (2020)."}],"event":{"name":"CIKM '22: The 31st ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Atlanta GA USA","acronym":"CIKM '22"},"container-title":["Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511808.3557441","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3511808.3557441","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:48:55Z","timestamp":1750182535000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511808.3557441"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,17]]},"references-count":32,"alternative-id":["10.1145\/3511808.3557441","10.1145\/3511808"],"URL":"https:\/\/doi.org\/10.1145\/3511808.3557441","relation":{},"subject":[],"published":{"date-parts":[[2022,10,17]]},"assertion":[{"value":"2022-10-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}