{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:20:51Z","timestamp":1750220451352,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":26,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T00:00:00Z","timestamp":1607299200000},"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":[[2020,12,7]]},"DOI":"10.1145\/3448891.3448893","type":"proceedings-article","created":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T01:43:00Z","timestamp":1628559780000},"page":"86-95","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Learned Taxi Fare for real-life trip trajectories via Temporal ResNet Exploration"],"prefix":"10.1145","author":[{"given":"Sayda","family":"Elmi","sequence":"first","affiliation":[{"name":"Singapore and 10"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tan","family":"Kian-Lee","sequence":"additional","affiliation":[{"name":"Singapore and 10"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,8,9]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_2_1_1","DOI":"10.1109\/TITS.2013.2290285"},{"volume-title":"IEEE International Instrumentation and Measurement Technology Conference Proceedings. 716\u2013721","author":"Bai Y.","unstructured":"Y. Bai and E. Wang . 2012. Design of taxi routing and fare estimation program with re-prediction methods for a smart phone . In IEEE International Instrumentation and Measurement Technology Conference Proceedings. 716\u2013721 . Y. Bai and E. Wang. 2012. Design of taxi routing and fare estimation program with re-prediction methods for a smart phone. In IEEE International Instrumentation and Measurement Technology Conference Proceedings. 716\u2013721.","key":"e_1_3_2_2_2_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_3_1","DOI":"10.1145\/1999995.2000006"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_4_1","DOI":"10.1109\/72.279181"},{"unstructured":"Brian Donovan and Dan Work. 2016. New York City Taxi Trip Data (2010-2013). https:\/\/doi.org\/10.13012\/J8PN93H8 10.13012\/J8PN93H8","key":"#cr-split#-e_1_3_2_2_5_1.1"},{"unstructured":"Brian Donovan and Dan Work. 2016. New York City Taxi Trip Data (2010-2013). https:\/\/doi.org\/10.13012\/J8PN93H8","key":"#cr-split#-e_1_3_2_2_5_1.2"},{"volume-title":"Supervised Sequence Labelling with Recurrent Neural Networks. Vol.\u00a0385","author":"Graves Alex","unstructured":"Alex Graves . 2012. Supervised Sequence Labelling with Recurrent Neural Networks. Vol.\u00a0385 . Springer . Alex Graves. 2012. Supervised Sequence Labelling with Recurrent Neural Networks. Vol.\u00a0385. Springer.","key":"e_1_3_2_2_6_1"},{"key":"e_1_3_2_2_7_1","volume-title":"Proceedings of IEEE International Joint Conference on Neural Networks., Vol.\u00a04. 2047\u20132052","volume":"4","author":"Graves A.","unstructured":"A. Graves and J. Schmidhuber . 2005. Framewise phoneme classification with bidirectional LSTM networks . In Proceedings of IEEE International Joint Conference on Neural Networks., Vol.\u00a04. 2047\u20132052 vol. 4 . A. Graves and J. Schmidhuber. 2005. Framewise phoneme classification with bidirectional LSTM networks. In Proceedings of IEEE International Joint Conference on Neural Networks., Vol.\u00a04. 2047\u20132052 vol. 4."},{"unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. CoRR abs\/1512.03385(2015).  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. CoRR abs\/1512.03385(2015).","key":"e_1_3_2_2_8_1"},{"key":"e_1_3_2_2_9_1","volume-title":"Proceedings of the 25th International Conference on Neural Information Processing Systems -","volume":"1105","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky , Ilya Sutskever , and Geoffrey\u00a0 E. Hinton . 2012 . ImageNet Classification with Deep Convolutional Neural Networks . In Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 1(NIPS). 1097\u2013 1105 . Alex Krizhevsky, Ilya Sutskever, and Geoffrey\u00a0E. Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 1(NIPS). 1097\u20131105."},{"key":"e_1_3_2_2_10_1","volume-title":"Proceedings of the 2015th International Conference on ECML PKDD Discovery Challenge. 63\u201374","author":"Lam Hoang\u00a0Thanh","year":"2015","unstructured":"Hoang\u00a0Thanh Lam , Ernesto Diaz-Aviles , Alessandra Pascale , Yiannis Gkoufas , and Bei Chen . 2015 . (Blue) Taxi Destination and Trip Time Prediction from Partial Trajectories . In Proceedings of the 2015th International Conference on ECML PKDD Discovery Challenge. 63\u201374 . Hoang\u00a0Thanh Lam, Ernesto Diaz-Aviles, Alessandra Pascale, Yiannis Gkoufas, and Bei Chen. 2015. (Blue) Taxi Destination and Trip Time Prediction from Partial Trajectories. In Proceedings of the 2015th International Conference on ECML PKDD Discovery Challenge. 63\u201374."},{"volume-title":"23rd Asia and South Pacific Design Automation Conference (ASP-DAC). 428\u2013433","author":"Liao S.","unstructured":"S. Liao , L. Zhou , X. Di , B. Yuan , and J. Xiong . 2018. Large-scale short-term urban taxi demand forecasting using deep learning . In 23rd Asia and South Pacific Design Automation Conference (ASP-DAC). 428\u2013433 . S. Liao, L. Zhou, X. Di, B. Yuan, and J. Xiong. 2018. Large-scale short-term urban taxi demand forecasting using deep learning. In 23rd Asia and South Pacific Design Automation Conference (ASP-DAC). 428\u2013433.","key":"e_1_3_2_2_11_1"},{"volume-title":"IEEE International Conference on Data Mining Workshop (ICDMW). 1109\u20131116","author":"Liu C.","unstructured":"C. Liu and Q. Qu . 2015. Trip Fare Estimation Study from Taxi Routing Behaviors and Localizing Traces . In IEEE International Conference on Data Mining Workshop (ICDMW). 1109\u20131116 . C. Liu and Q. Qu. 2015. Trip Fare Estimation Study from Taxi Routing Behaviors and Localizing Traces. In IEEE International Conference on Data Mining Workshop (ICDMW). 1109\u20131116.","key":"e_1_3_2_2_12_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_13_1","DOI":"10.24963\/ijcai.2018\/482"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_14_1","DOI":"10.3390\/s17040818"},{"unstructured":"Rishabh Upadhyay and Simon Lui. 2017. Taxi Fare Rate Classification Using Deep Networks.  Rishabh Upadhyay and Simon Lui. 2017. Taxi Fare Rate Classification Using Deep Networks.","key":"e_1_3_2_2_15_1"},{"volume-title":"DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. In IEEE 33rd International Conference on Data Engineering (ICDE). 243\u2013254","author":"Wang D.","unstructured":"D. Wang , W. Cao , J. Li , and J. Ye . 2017 . DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. In IEEE 33rd International Conference on Data Engineering (ICDE). 243\u2013254 . D. Wang, W. Cao, J. Li, and J. Ye. 2017. DeepSD: Supply-Demand Prediction for Online Car-Hailing Services Using Deep Neural Networks. In IEEE 33rd International Conference on Data Engineering (ICDE). 243\u2013254.","key":"e_1_3_2_2_16_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_17_1","DOI":"10.1145\/2996913.2996943"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_18_1","DOI":"10.1145\/3219819.3219900"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_19_1","DOI":"10.24963\/ijcai.2017\/430"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_20_1","DOI":"10.24963\/ijcai.2017\/430"},{"key":"e_1_3_2_2_21_1","volume-title":"Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI,USA. 5668\u20135675","author":"Yao Huaxiu","year":"2019","unstructured":"Huaxiu Yao , Xianfeng Tang , Hua Wei , Guanjie Zheng , and Zhenhui Li . 2019 . Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI,USA. 5668\u20135675 . Huaxiu Yao, Xianfeng Tang, Hua Wei, Guanjie Zheng, and Zhenhui Li. 2019. Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI,USA. 5668\u20135675."},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_22_1","DOI":"10.1609\/aaai.v32i1.11836"},{"doi-asserted-by":"crossref","unstructured":"Hanyuan Zhang Hao Wu Weiwei Sun and Baihua Zheng. 2018. DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision. In IJCAI.  Hanyuan Zhang Hao Wu Weiwei Sun and Baihua Zheng. 2018. DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision. In IJCAI.","key":"e_1_3_2_2_23_1","DOI":"10.24963\/ijcai.2018\/508"},{"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.  Junbo Zhang Yu Zheng and Dekang Qi. 2017. Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction. In AAAI.","key":"e_1_3_2_2_24_1","DOI":"10.1609\/aaai.v31i1.10735"},{"doi-asserted-by":"publisher","key":"e_1_3_2_2_25_1","DOI":"10.1145\/2629592"}],"event":{"acronym":"MobiQuitous '20","name":"MobiQuitous '20: Computing, Networking and Services","location":"Darmstadt Germany"},"container-title":["MobiQuitous 2020 - 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3448891.3448893","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3448891.3448893","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:54Z","timestamp":1750193274000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3448891.3448893"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,7]]},"references-count":26,"alternative-id":["10.1145\/3448891.3448893","10.1145\/3448891"],"URL":"https:\/\/doi.org\/10.1145\/3448891.3448893","relation":{},"subject":[],"published":{"date-parts":[[2020,12,7]]},"assertion":[{"value":"2021-08-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}