{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T01:43:15Z","timestamp":1787017395258,"version":"3.56.0"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T00:00:00Z","timestamp":1531958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Southwest Jiaotong University","award":["Cultivation Program for the Excellent Doctoral Dissertation"],"award-info":[{"award-number":["Cultivation Program for the Excellent Doctoral Dissertation"]}]},{"name":"National Natural Science Foundation of China","award":["U1609217"],"award-info":[{"award-number":["U1609217"]}]},{"name":"National Natural Science Foundation of China","award":["61773324"],"award-info":[{"award-number":["61773324"]}]},{"name":"National Natural Science Foundation of China","award":["61672399"],"award-info":[{"award-number":["61672399"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,7,19]]},"DOI":"10.1145\/3219819.3219822","type":"proceedings-article","created":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T09:05:12Z","timestamp":1531991112000},"page":"965-973","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":243,"title":["Deep Distributed Fusion Network for Air Quality Prediction"],"prefix":"10.1145","author":[{"given":"Xiuwen","family":"Yi","sequence":"first","affiliation":[{"name":"Southwest Jiaotong University &JD Finance, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"JD Finance &Southwest Jiaotong University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Southwest Jiaotong University &JD Finance, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianrui","family":"Li","sequence":"additional","affiliation":[{"name":"Southwest Jiaotong University, Chengdu, Sichuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zheng","sequence":"additional","affiliation":[{"name":"JD Finance, Southwest Jiaotong University &Xidian University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,7,19]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Global air quality and pollution. Science 302.5651","author":"Hajime Akimoto","year":"2003","unstructured":"Akimoto Hajime . 2003. Global air quality and pollution. Science 302.5651 ( 2003 ), 1716--1719. Akimoto Hajime. 2003. Global air quality and pollution. Science 302.5651 (2003), 1716--1719."},{"key":"e_1_3_2_1_2_1","volume-title":"Human health effects of air pollution. Environmental pollution 151, 2","author":"Marilena Kampa","year":"2008","unstructured":"Kampa Marilena , and Elias Castanas . 2008. Human health effects of air pollution. Environmental pollution 151, 2 ( 2008 ), 362--367. Kampa Marilena, and Elias Castanas. 2008. Human health effects of air pollution. Environmental pollution 151, 2 (2008), 362--367."},{"key":"e_1_3_2_1_3_1","volume-title":"A Gaussian Bayesian Model to Identify Spatio-temporal Causalities for Air Pollution based on Urban Big Data","author":"Zhu Julie Yixuan","unstructured":"Julie Yixuan Zhu , Yu Zheng , Xiuwen Yi , Victor O.K. Li. 2016. A Gaussian Bayesian Model to Identify Spatio-temporal Causalities for Air Pollution based on Urban Big Data . In INFOCOM WKSHPS. IEEE , 3--8. Julie Yixuan Zhu, Yu Zheng, Xiuwen Yi, Victor O.K. Li. 2016. A Gaussian Bayesian Model to Identify Spatio-temporal Causalities for Air Pollution based on Urban Big Data. In INFOCOM WKSHPS. IEEE, 3--8."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488188"},{"key":"e_1_3_2_1_5_1","unstructured":"Jianyi Lu and Xin Cao. 2015. PM2.5 Pollution in major cities in China: pollution status emission sources and control measures. Fresenius Environmental Bulletin 24 4A (2014): 1338--1349.  Jianyi Lu and Xin Cao. 2015. PM2.5 Pollution in major cities in China: pollution status emission sources and control measures. Fresenius Environmental Bulletin 24 4A (2014): 1338--1349."},{"key":"e_1_3_2_1_6_1","volume-title":"Analyzing air pollution on the urban environment","author":"Baralis Elena","unstructured":"Elena Baralis , Tania Cerquitelli , Silvia Chiusano , Paolo Garza , and Mohammad Reza Kavoosifar . 2016. Analyzing air pollution on the urban environment . In MIPRO. IEEE , 1464--1469. Elena Baralis, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, and Mohammad Reza Kavoosifar. 2016. Analyzing air pollution on the urban environment. In MIPRO. IEEE, 1464--1469."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788573"},{"key":"e_1_3_2_1_8_1","unstructured":"AirPollutionPrediction Website: http:\/\/airprediction.urban-computing.com.  AirPollutionPrediction Website: http:\/\/airprediction.urban-computing.com."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2996916"},{"key":"e_1_3_2_1_10_1","unstructured":"Xiuwen Yi Yu Zheng Junbo Zhang Tianrui Li. 2015. ST-MVL: Filling Missing Values in Geo-sensory Time Series Data. In IJCAI. 2704--2710.   Xiuwen Yi Yu Zheng Junbo Zhang Tianrui Li. 2015. ST-MVL: Filling Missing Values in Geo-sensory Time Series Data. In IJCAI. 2704--2710."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2007.07.010"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.2307\/143141"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Junbo Zhang Yu Zheng and Dekang Qi. 2017. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction. In AAAI 1655--1661.  Junbo Zhang Yu Zheng and Dekang Qi. 2017. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction. In AAAI 1655--1661.","DOI":"10.1609\/aaai.v31i1.10735"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2997016"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Junbo Zhang Yu Zheng Dekang Qi Ruiyuan Li Xiuwen Yi Tianrui Li. 2018. Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks. Artificial Intelligence 259 (2018) 147--166 Junbo Zhang Yu Zheng Dekang Qi Ruiyuan Li Xiuwen Yi Tianrui Li. 2018. Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks. Artificial Intelligence 259 (2018) 147--166","DOI":"10.1016\/j.artint.2018.03.002"},{"key":"e_1_3_2_1_17_1","unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. DeepFM: 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. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. arXiv preprint arXiv:1703.04247 (2017)."},{"key":"e_1_3_2_1_18_1","volume-title":"Fast and accurate deep network learning by exponential linear units (ELUs). arXiv preprint arXiv, 1511.07289","author":"Clevert Djork-Arne","year":"2015","unstructured":"Djork-Arne Clevert , Thomas Unterthiner , and Sepp Hochreiter . 2015. Fast and accurate deep network learning by exponential linear units (ELUs). arXiv preprint arXiv, 1511.07289 ( 2015 ). Djork-Arne Clevert, Thomas Unterthiner, and Sepp Hochreiter. 2015. Fast and accurate deep network learning by exponential linear units (ELUs). arXiv preprint arXiv, 1511.07289 (2015)."},{"key":"e_1_3_2_1_19_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv, 1412.6980.","author":"Diederik Kingma","year":"2014","unstructured":"Kingma Diederik , and Ba Jimmy . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv, 1412.6980. Kingma Diederik, and Ba Jimmy. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv, 1412.6980."},{"key":"e_1_3_2_1_20_1","unstructured":"Srivastava Nitish Geoffrey E. Hinton Alex Krizhevsky Ilya Sutskever and Ruslan Salakhutdinov. Dropout: a simple way to prevent neural networks from overfitting. Journal of machine learning research 15 1 (2014): 1929--1958.   Srivastava Nitish Geoffrey E. Hinton Alex Krizhevsky Ilya Sutskever and Ruslan Salakhutdinov. Dropout: a simple way to prevent neural networks from overfitting. Journal of machine learning research 15 1 (2014): 1929--1958."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Dong Wang Junbo Zhang Wei Cao Jian Li Yu Zheng. 2018. When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks. In AAAI.  Dong Wang Junbo Zhang Wei Cao Jian Li Yu Zheng. 2018. When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks. In AAAI.","DOI":"10.1609\/aaai.v32i1.11877"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Dong Wang Wei Cao Jian Li Jieping Ye. 2017. DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. In ICDE. IEEE 243--254.  Dong Wang Wei Cao Jian Li Jieping Ye. 2017. DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. In ICDE. IEEE 243--254.","DOI":"10.1109\/ICDE.2017.83"},{"key":"e_1_3_2_1_23_1","volume-title":"Atmospheric Environment, 60","author":"Zhang Yang","year":"2012","unstructured":"Yang Zhang , Bocquet Marc , Mallet Vivien , Seigneur Christian and Baklanov Alexander. 2012 a. Real-time Air Quality Forecasting, Part I: History, techniques, and current status , Atmospheric Environment, 60 , ( 2012 ), 632--655. Yang Zhang, Bocquet Marc, Mallet Vivien, Seigneur Christian and Baklanov Alexander. 2012 a. Real-time Air Quality Forecasting, Part I: History, techniques, and current status, Atmospheric Environment, 60, (2012), 632--655."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2012.02.041"},{"key":"e_1_3_2_1_25_1","unstructured":"Xuan Song Kanasugi Hiroshi and Shibasaki Ryosuke. 2016. DeepTransport: Prediction and simulation of human mobility and transport mode at a citywide level. In AAAI. 2618--2624.   Xuan Song Kanasugi Hiroshi and Shibasaki Ryosuke. 2016. DeepTransport: Prediction and simulation of human mobility and transport mode at a citywide level. In AAAI. 2618--2624."},{"key":"e_1_3_2_1_26_1","unstructured":"Huaxiu Yao Fei Wu Jintao Ke Xianfeng Tang Yitian Jia Siyu Lu Pinghua Gong Jieping Ye Zhenhui Li. 2018. Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. In AAAI.  Huaxiu Yao Fei Wu Jintao Ke Xianfeng Tang Yitian Jia Siyu Lu Pinghua Gong Jieping Ye Zhenhui Li. 2018. Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction. In AAAI."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Yuxuan Liang Songyu Ke Junbo Zhang Xiuwen Yi Yu Zheng. 2018. Multi-level Attention Networks for Geo-sensory Time Series Prediction. In IJCAI.  Yuxuan Liang Songyu Ke Junbo Zhang Xiuwen Yi Yu Zheng. 2018. Multi-level Attention Networks for Geo-sensory Time Series Prediction. In IJCAI.","DOI":"10.24963\/ijcai.2018\/476"}],"event":{"name":"KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","location":"London United Kingdom","acronym":"KDD '18","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 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3219822","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3219819.3219822","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:08:43Z","timestamp":1750194523000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3219822"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,19]]},"references-count":27,"alternative-id":["10.1145\/3219819.3219822","10.1145\/3219819"],"URL":"https:\/\/doi.org\/10.1145\/3219819.3219822","relation":{},"subject":[],"published":{"date-parts":[[2018,7,19]]},"assertion":[{"value":"2018-07-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}