{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T02:44:01Z","timestamp":1783737841290,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T00:00:00Z","timestamp":1595635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,7,25]]},"DOI":"10.1145\/3397271.3401082","type":"proceedings-article","created":{"date-parts":[[2020,7,25]],"date-time":"2020-07-25T07:50:08Z","timestamp":1595663408000},"page":"199-208","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":41,"title":["AutoGroup"],"prefix":"10.1145","author":[{"given":"Bin","family":"Liu","sequence":"first","affiliation":[{"name":"Bytedance & Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niannan","family":"Xue","sequence":"additional","affiliation":[{"name":"Imperial College London, London, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huifeng","family":"Guo","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiming","family":"Tang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanos","family":"Zafeiriou","sequence":"additional","affiliation":[{"name":"Imperial College London, London, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuqiang","family":"He","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenguo","family":"Li","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,7,25]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159727"},{"key":"e_1_3_2_2_2_1","unstructured":"Mathieu Blondel Akinori Fujino Naonori Ueda and Masakazu Ishihata. 2016. Higher-order factorization machines. In Advances in Neural Information Processing Systems. 3351--3359.  Mathieu Blondel Akinori Fujino Naonori Ueda and Masakazu Ishihata. 2016. Higher-order factorization machines. In Advances in Neural Information Processing Systems. 3351--3359."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/1756006.1859899"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_2_5_1","volume-title":"Wide & Deep Learning for Recommender Systems. conference on recommender systems","author":"Cheng Hengtze","year":"2016","unstructured":"Hengtze Cheng , Levent Koc , Jeremiah Harmsen , Tal Shaked , Tushar Deepak Chandra , Hrishi Aradhye , Glen Anderson , Greg S Corrado , Wei Chai , Mustafa Ispir , 2016 . Wide & Deep Learning for Recommender Systems. conference on recommender systems (2016), 7--10. Hengtze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Deepak Chandra, Hrishi Aradhye, Glen Anderson, Greg S Corrado, Wei Chai, Mustafa Ispir, et al. 2016. Wide & Deep Learning for Recommender Systems. conference on recommender systems (2016), 7--10."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_2_7_1","volume-title":"Jan Hendrik Metzen, and Frank Hutter","author":"Elsken Thomas","year":"2018","unstructured":"Thomas Elsken , Jan Hendrik Metzen, and Frank Hutter . 2018 . Neural architecture search: A survey. arXiv preprint arXiv:1808.05377 (2018). Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter. 2018. Neural architecture search: A survey. arXiv preprint arXiv:1808.05377 (2018)."},{"key":"e_1_3_2_2_8_1","volume-title":"Jan Hendrik Metzen, and Frank Hutter","author":"Elsken Thomas","year":"2018","unstructured":"Thomas Elsken , Jan Hendrik Metzen, and Frank Hutter . 2018 . Neural architecture search: A survey. arXiv preprint arXiv:1808.05377 (2018). Thomas Elsken, Jan Hendrik Metzen, and Frank Hutter. 2018. Neural architecture search: A survey. arXiv preprint arXiv:1808.05377 (2018)."},{"key":"e_1_3_2_2_9_1","volume-title":"Deep fm: a factorization-machine based neural network for ctr prediction. arXiv preprint arXiv:1703.04247","author":"Guo Huifeng","year":"2017","unstructured":"Huifeng Guo , Ruiming Tang , Yunming Ye , Zhenguo Li , and Xiuqiang He. 2017. Deep fm: a factorization-machine based neural network for ctr prediction. arXiv preprint arXiv:1703.04247 ( 2017 ). Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He. 2017. Deep fm: a factorization-machine based neural network for ctr prediction. arXiv preprint arXiv:1703.04247 (2017)."},{"key":"e_1_3_2_2_10_1","unstructured":"Xiangnan He and TatSeng Chua. 2017. Neural Factorization Machines for Sparse Predictive Analytics. (2017) 355--364.  Xiangnan He and TatSeng Chua. 2017. Neural Factorization Machines for Sparse Predictive Analytics. (2017) 355--364."},{"key":"e_1_3_2_2_11_1","volume-title":"Eighth International Workshop on Data Mining for Online Advertising. 1--9.","author":"He Xinran","unstructured":"Xinran He , Junfeng Pan , Ou Jin , Tianbing Xu , Bo Liu , Tao Xu , Yanxin Shi , Antoine Atallah , Ralf Herbrich , and Stuart Bowers .2014. Practical Lessons from Predicting Clicks on Ads at Facebook . In Eighth International Workshop on Data Mining for Online Advertising. 1--9. Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, and Stuart Bowers.2014. Practical Lessons from Predicting Clicks on Ads at Facebook. In Eighth International Workshop on Data Mining for Online Advertising. 1--9."},{"key":"e_1_3_2_2_12_1","volume-title":"Multilayer feed forward networks are universal approximators. Neural networks 2, 5","author":"Hornik Kurt","year":"1989","unstructured":"Kurt Hornik , Maxwell Stinchcombe , and Halbert White . 1989. Multilayer feed forward networks are universal approximators. Neural networks 2, 5 ( 1989 ), 359--366. Kurt Hornik, Maxwell Stinchcombe, and Halbert White. 1989. Multilayer feed forward networks are universal approximators. Neural networks 2, 5 (1989), 359--366."},{"key":"e_1_3_2_2_13_1","volume-title":"Categorical reparameterization with gumbel-softmax. arXiv preprint arXiv:1611.01144","author":"Jang Eric","year":"2016","unstructured":"Eric Jang , Shixiang Gu , and Ben Poole . 2016. Categorical reparameterization with gumbel-softmax. arXiv preprint arXiv:1611.01144 ( 2016 ). Eric Jang, Shixiang Gu, and Ben Poole. 2016. Categorical reparameterization with gumbel-softmax. arXiv preprint arXiv:1611.01144 (2016)."},{"key":"e_1_3_2_2_14_1","volume-title":"Field-aware Factorization Machines for CTR Prediction. In ACM Conference on Recommender Systems. 43--50","author":"Juan Yuchin","year":"2016","unstructured":"Yuchin Juan , Yong Zhuang , Wei Sheng Chin , and Chih Jen Lin . 2016 . Field-aware Factorization Machines for CTR Prediction. In ACM Conference on Recommender Systems. 43--50 . Yuchin Juan, Yong Zhuang, Wei Sheng Chin, and Chih Jen Lin. 2016. Field-aware Factorization Machines for CTR Prediction. In ACM Conference on Recommender Systems. 43--50."},{"key":"e_1_3_2_2_15_1","volume-title":"Acm Sigkdd International Conference on Knowledge Discovery & Data Mining. 768--776","author":"Lee Kuang Chih","year":"2012","unstructured":"Kuang Chih Lee , Burkay Orten , Ali Dasdan , and Wentong Li . 2012 . Estimating conversion rate in display advertising from past performance data . In Acm Sigkdd International Conference on Knowledge Discovery & Data Mining. 768--776 . Kuang Chih Lee, Burkay Orten, Ali Dasdan, and Wentong Li. 2012. Estimating conversion rate in display advertising from past performance data. In Acm Sigkdd International Conference on Knowledge Discovery & Data Mining. 768--776."},{"key":"e_1_3_2_2_16_1","volume-title":"xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems. arXiv preprint arXiv:1803.05170","author":"Lian Jianxun","year":"2018","unstructured":"Jianxun Lian , Xiaohuan Zhou , Fuzheng Zhang , Zhongxia Chen , Xing Xie , and Guangzhong Sun . 2018. xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems. arXiv preprint arXiv:1803.05170 ( 2018 ). Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang, Zhongxia Chen, Xing Xie, and Guangzhong Sun. 2018. xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems. arXiv preprint arXiv:1803.05170 (2018)."},{"key":"e_1_3_2_2_17_1","volume-title":"Matthew Wiener, et al","author":"Liaw Andy","year":"2002","unstructured":"Andy Liaw , Matthew Wiener, et al . 2002 . Classification and regression by random Forest. R news2, 3 (2002), 18--22. Andy Liaw, Matthew Wiener, et al. 2002. Classification and regression by random Forest. R news2, 3 (2002), 18--22."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Bin Liu Ruiming Tang Yingzhi Chen Jinkai Yu Huifeng Guo and Yuzhou Zhang. 2019. Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. www2019. (2019). https:\/\/doi.org\/10.1145\/3308558.3313497 arXiv:arXiv:1904.04447  Bin Liu Ruiming Tang Yingzhi Chen Jinkai Yu Huifeng Guo and Yuzhou Zhang. 2019. Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. www2019. (2019). https:\/\/doi.org\/10.1145\/3308558.3313497 arXiv:arXiv:1904.04447","DOI":"10.1145\/3308558.3313497"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_2"},{"key":"e_1_3_2_2_20_1","volume-title":"Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055","author":"Liu Hanxiao","year":"2018","unstructured":"Hanxiao Liu , Karen Simonyan , and Yiming Yang . 2018 . Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055 (2018). Hanxiao Liu, Karen Simonyan, and Yiming Yang. 2018. Darts: Differentiable architecture search. arXiv preprint arXiv:1806.09055 (2018)."},{"key":"e_1_3_2_2_21_1","unstructured":"Renqian Luo Fei Tian Tao Qin Enhong Chen and Tie-Yan Liu. 2018. Neural architecture optimization. In Advances in neural information processing systems. 7816--7827.  Renqian Luo Fei Tian Tao Qin Enhong Chen and Tie-Yan Liu. 2018. Neural architecture optimization. In Advances in neural information processing systems. 7816--7827."},{"key":"e_1_3_2_2_22_1","unstructured":"Chris J Maddison Daniel Tarlow and Tom Minka. 2014. A* sampling. In Advances in Neural Information Processing Systems. 3086--3094.  Chris J Maddison Daniel Tarlow and Tom Minka. 2014. A* sampling. In Advances in Neural Information Processing Systems. 3086--3094."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488200"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186040"},{"key":"e_1_3_2_2_25_1","volume-title":"Efficient neural architecture search via parameter sharing. arXiv preprint arXiv:1802.03268","author":"Pham Hieu","year":"2018","unstructured":"Hieu Pham , Melody Y Guan , Barret Zoph , Quoc V Le , and Jeff Dean . 2018. Efficient neural architecture search via parameter sharing. arXiv preprint arXiv:1802.03268 ( 2018 ). Hieu Pham, Melody Y Guan, Barret Zoph, Quoc VLe, and Jeff Dean. 2018. Efficient neural architecture search via parameter sharing. arXiv preprint arXiv:1802.03268 (2018)."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0151"},{"key":"e_1_3_2_2_27_1","volume-title":"Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. arXiv preprint arXiv:1807.00311","author":"Qu Yanru","year":"2018","unstructured":"Yanru Qu , Bohui Fang , Weinan Zhang , Ruiming Tang , Minzhe Niu , Huifeng Guo , Yong Yu , and Xiuqiang He. 2018. Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. arXiv preprint arXiv:1807.00311 ( 2018 ). Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, and Xiuqiang He. 2018. Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. arXiv preprint arXiv:1807.00311 (2018)."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.127"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168771"},{"key":"e_1_3_2_2_31_1","unstructured":"Guangzhong Sun Guangzhong Sun Guangzhong Sun Guangzhong Sun Guangzhong Sun and Guangzhong Sun. 2017. Practical Lessons for Job Recommendations in the Cold-Start Scenario. In Recommender Systems Challenge. 4.  Guangzhong Sun Guangzhong Sun Guangzhong Sun Guangzhong Sun Guangzhong Sun and Guangzhong Sun. 2017. Practical Lessons for Job Recommendations in the Cold-Start Scenario. In Recommender Systems Challenge. 4."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01099"},{"key":"e_1_3_2_2_34_1","volume-title":"Attentional factorization machines: Learning the weight of feature interactions via attention networks. arXiv preprint arXiv:1708.04617","author":"Xiao Jun","year":"2017","unstructured":"Jun Xiao , Hao Ye , Xiangnan He , Hanwang Zhang , Fei Wu , and Tat-Seng Chua . 2017. Attentional factorization machines: Learning the weight of feature interactions via attention networks. arXiv preprint arXiv:1708.04617 ( 2017 ). Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. 2017. Attentional factorization machines: Learning the weight of feature interactions via attention networks. arXiv preprint arXiv:1708.04617 (2017)."},{"key":"e_1_3_2_2_35_1","volume-title":"SNAS: stochastic neural architecture search. arXiv preprint arXiv:1812.09926","author":"Xie Sirui","year":"2018","unstructured":"Sirui Xie , Hehui Zheng , Chunxiao Liu , and Liang Lin . 2018. SNAS: stochastic neural architecture search. arXiv preprint arXiv:1812.09926 ( 2018 ). Sirui Xie, Hehui Zheng, Chunxiao Liu, and Liang Lin. 2018. SNAS: stochastic neural architecture search. arXiv preprint arXiv:1812.09926 (2018)."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianming Du and Jun Wang. 2016. Deep Learning over Multifield Categorical Data. (2016).  Weinan Zhang Tianming Du and Jun Wang. 2016. Deep Learning over Multifield Categorical Data. (2016).","DOI":"10.1007\/978-3-319-30671-1_4"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianming Du and Jun Wang. 2016. Deep Learning over Multifield Categorical Data: A Case Study on User Response Prediction. (2016).  Weinan Zhang Tianming Du and Jun Wang. 2016. Deep Learning over Multifield Categorical Data: A Case Study on User Response Prediction. (2016).","DOI":"10.1007\/978-3-319-30671-1_4"},{"key":"e_1_3_2_2_38_1","volume-title":"You only search once: Single shot neural architecture search via direct sparse optimization. arXiv preprint arXiv:1811.01567","author":"Zhang Xinbang","year":"2018","unstructured":"Xinbang Zhang , Zehao Huang , and Naiyan Wang . 2018. You only search once: Single shot neural architecture search via direct sparse optimization. arXiv preprint arXiv:1811.01567 ( 2018 ). Xinbang Zhang, Zehao Huang, and Naiyan Wang. 2018. You only search once: Single shot neural architecture search via direct sparse optimization. arXiv preprint arXiv:1811.01567 (2018)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"}],"event":{"name":"SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval","location":"Virtual Event China","acronym":"SIGIR '20","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401082","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3397271.3401082","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:38Z","timestamp":1750195898000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3397271.3401082"}},"subtitle":["Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction"],"short-title":[],"issued":{"date-parts":[[2020,7,25]]},"references-count":40,"alternative-id":["10.1145\/3397271.3401082","10.1145\/3397271"],"URL":"https:\/\/doi.org\/10.1145\/3397271.3401082","relation":{},"subject":[],"published":{"date-parts":[[2020,7,25]]},"assertion":[{"value":"2020-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}