{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:34:57Z","timestamp":1762508097638,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,2,15]],"date-time":"2020-02-15T00:00:00Z","timestamp":1581724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012659","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971382"],"award-info":[{"award-number":["61971382"]}],"id":[{"id":"10.13039\/501100012659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,2,15]]},"DOI":"10.1145\/3383972.3383991","type":"proceedings-article","created":{"date-parts":[[2020,5,26]],"date-time":"2020-05-26T18:15:22Z","timestamp":1590516922000},"page":"1-5","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["An Attention-based Deep Network for CTR Prediction"],"prefix":"10.1145","author":[{"given":"Hailong","family":"Zhang","sequence":"first","affiliation":[{"name":"Communication University of China, Beijing, China"}]},{"given":"Jinyao","family":"Yan","sequence":"additional","affiliation":[{"name":"Communication University of China, Beijing, China"}]},{"given":"Yuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Communication University of China, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2020,5,26]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_1_1_1","DOI":"10.1145\/2487575.2488200"},{"key":"e_1_3_2_1_2_1","article-title":"Simple and scalable response prediction for display advertising","volume":"5","author":"Chapelle O.","year":"2014","unstructured":"Chapelle , O. , Manavoglu , E. , & Rosales , R. 2014 . Simple and scalable response prediction for display advertising . ACM Transactions on Intelligent Systems and Technology , 5 , 4, (Jan. 2015), 1--34. Chapelle, O., Manavoglu, E., & Rosales, R. 2014. Simple and scalable response prediction for display advertising. ACM Transactions on Intelligent Systems and Technology, 5, 4, (Jan. 2015), 1--34.","journal-title":"ACM Transactions on Intelligent Systems and Technology"},{"key":"e_1_3_2_1_3_1","volume-title":"Factorization Machines. IEEE International Conference on Data Mining.","author":"Rendle S.","year":"2011","unstructured":"Rendle , S. 2011 . Factorization Machines. IEEE International Conference on Data Mining. ( Sydney, Australia , Dec. 13-17, 2010). IEEE, 995--1000. Rendle, S. 2011. Factorization Machines. IEEE International Conference on Data Mining. (Sydney, Australia, Dec. 13-17, 2010). IEEE, 995--1000."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1145\/2556195.2556240"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_5_1","DOI":"10.1145\/2648584.2648589"},{"key":"e_1_3_2_1_6_1","first-page":"6","article-title":"ImageNet Classification with Deep Convolutional Neural Networks","volume":"60","author":"Krizhevsky A.","year":"2012","unstructured":"Krizhevsky , A. , Sutskever , I. , & Hinton , G. 2012 . ImageNet Classification with Deep Convolutional Neural Networks . Communications of the ACM. 60 , 6 (Jun. 2017), 84--90. Krizhevsky, A., Sutskever, I., & Hinton, G. 2012. ImageNet Classification with Deep Convolutional Neural Networks. Communications of the ACM. 60, 6 (Jun. 2017), 84--90.","journal-title":"Communications of the ACM."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_7_1","DOI":"10.1145\/2661829.2661935"},{"key":"e_1_3_2_1_8_1","volume-title":"Deep learning over multifield categorical data. Advances in Information Retrieval. ECIR","author":"Zhang W.","year":"2016","unstructured":"Zhang W. , Du T. , Wang J. 2016. Deep learning over multifield categorical data. Advances in Information Retrieval. ECIR 2016 . Lecture Notes in Computer Science, vol 9626. Springer , Cham, 45--57. Zhang W., Du T., Wang J. 2016. Deep learning over multifield categorical data. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science, vol 9626. Springer, Cham, 45--57."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_9_1","DOI":"10.1145\/2988450.2988454"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_10_1","DOI":"10.5555\/3172077.3172127"},{"doi-asserted-by":"crossref","unstructured":"Cho K. Van Merri\u00ebnboer B. Gulcehre C. Bahdanau D. Bougares F. Schwenk H. and Bengio Y. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078.  Cho K. Van Merri\u00ebnboer B. Gulcehre C. Bahdanau D. Bougares F. Schwenk H. and Bengio Y. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078.","key":"e_1_3_2_1_11_1","DOI":"10.3115\/v1\/D14-1179"},{"unstructured":"Bahdanau D. Cho K. and Bengio Y. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.  Bahdanau D. Cho K. and Bengio Y. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.","key":"e_1_3_2_1_12_1"},{"key":"e_1_3_2_1_13_1","volume-title":"Long short-term memory. Neural Computation, 9, 8, (Nov","author":"Hochreiter S.","year":"1997","unstructured":"Hochreiter , S. , & Schmidhuber , J\u00fcrgen, J. 1997. Long short-term memory. Neural Computation, 9, 8, (Nov . 1997 ), 1735--1780. Hochreiter, S., & Schmidhuber, J\u00fcrgen, J. 1997. Long short-term memory. Neural Computation, 9, 8, (Nov. 1997), 1735--1780."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 27th International Conference on Neural Information Processing Systems.","author":"Sutskever I.","year":"2014","unstructured":"Sutskever , I. , Vinyals , O. , & Le , Q. V. 2014 . Sequence to sequence learning with neural networks . Proceedings of the 27th International Conference on Neural Information Processing Systems. ( Montreal, Canada , December 08-13, 2014). MIT Press Cambridge, MA, USA, 3104--3112 Sutskever, I., Vinyals, O., & Le, Q. V. 2014. Sequence to sequence learning with neural networks. Proceedings of the 27th International Conference on Neural Information Processing Systems. (Montreal, Canada, December 08-13, 2014). MIT Press Cambridge, MA, USA, 3104--3112"},{"unstructured":"Bahdanau D. Cho K. and Bengio Y. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.  Bahdanau D. Cho K. and Bengio Y. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.","key":"e_1_3_2_1_15_1"},{"doi-asserted-by":"crossref","unstructured":"Luong M.T. Pham H. and Manning C.D. 2015. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025.  Luong M.T. Pham H. and Manning C.D. 2015. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025.","key":"e_1_3_2_1_16_1","DOI":"10.18653\/v1\/D15-1166"},{"key":"e_1_3_2_1_17_1","volume-title":"Rectified Linear Units Improve Restricted Boltzmann Machines Vinod Nair. Proceedings of the 27th International Conference on International Conference on Machine Learning.","author":"Nair V.","year":"2010","unstructured":"Nair , V. and Hinton , G.E ., 2010 . Rectified Linear Units Improve Restricted Boltzmann Machines Vinod Nair. Proceedings of the 27th International Conference on International Conference on Machine Learning. ( Haifa, Israel , June 21-24, 2010 ). Omnipress, USA, 807--814. Nair, V. and Hinton, G.E., 2010. Rectified Linear Units Improve Restricted Boltzmann Machines Vinod Nair. Proceedings of the 27th International Conference on International Conference on Machine Learning. (Haifa, Israel, June 21-24, 2010). Omnipress, USA, 807--814."},{"key":"e_1_3_2_1_18_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980.","author":"Kingma D.P.","year":"2014","unstructured":"Kingma , D.P. and Ba , J. , 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980. Kingma, D.P. and Ba, J., 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980."},{"doi-asserted-by":"crossref","unstructured":"Akimova T. Levine M.H. Beier U.H. and Hancock W.W. 2016. Standardization evaluation and area-under-curve analysis of human and murine Treg suppressive function. In Suppression and Regulation of Immune Responses. Humana Press New York NY 43--78.  Akimova T. Levine M.H. Beier U.H. and Hancock W.W. 2016. Standardization evaluation and area-under-curve analysis of human and murine Treg suppressive function. In Suppression and Regulation of Immune Responses. Humana Press New York NY 43--78.","key":"e_1_3_2_1_19_1","DOI":"10.1007\/978-1-4939-3139-2_4"}],"event":{"sponsor":["Shenzhen University Shenzhen University"],"acronym":"ICMLC 2020","name":"ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing","location":"Shenzhen China"},"container-title":["Proceedings of the 2020 12th International Conference on Machine Learning and Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3383972.3383991","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3383972.3383991","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:33:23Z","timestamp":1750199603000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3383972.3383991"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,15]]},"references-count":19,"alternative-id":["10.1145\/3383972.3383991","10.1145\/3383972"],"URL":"https:\/\/doi.org\/10.1145\/3383972.3383991","relation":{},"subject":[],"published":{"date-parts":[[2020,2,15]]},"assertion":[{"value":"2020-05-26","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}