{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T01:00:01Z","timestamp":1759971601883,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T00:00:00Z","timestamp":1730160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,29]]},"DOI":"10.1145\/3681771.3699917","type":"proceedings-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T09:59:22Z","timestamp":1734343162000},"page":"42-45","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Personalized and On-device Trajectory Mobility Prediction"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4565-8418","authenticated-orcid":false,"given":"Cuauhtemoc","family":"Anda","sequence":"first","affiliation":[{"name":"NCS, Sinapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2092-3841","authenticated-orcid":false,"given":"Ning","family":"Cao","sequence":"additional","affiliation":[{"name":"College of Computing & Data Science, NTU Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9566-3127","authenticated-orcid":false,"given":"Shuai","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computing & Data Science, NTU Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6372-408X","authenticated-orcid":false,"given":"Shaowei","family":"Ying","sequence":"additional","affiliation":[{"name":"NCS, Sinapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4430-6373","authenticated-orcid":false,"given":"Gao","family":"Cong","sequence":"additional","affiliation":[{"name":"College of Computing & Data Science, NTU Singapore"}]}],"member":"320","published-online":{"date-parts":[[2024,12,16]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2923-3"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MWSCAS.2017.8053243"},{"key":"e_1_3_2_1_3_1","first-page":"18932","article-title":"Revisiting deep learning models for tabular data","volume":"34","author":"Gorishniy Yury","year":"2021","unstructured":"Yury Gorishniy, Ivan Rubachev, Valentin Khrulkov, and Artem Babenko. Revisiting deep learning models for tabular data. Advances in Neural Information Processing Systems, 34:18932--18943, 2021.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_4_1","volume-title":"Why do tree-based models still outperform deep learning on typical tabular data? Advances in neural information processing systems, 35:507--520","author":"Grinsztajn L\u00e9o","year":"2022","unstructured":"L\u00e9o Grinsztajn, Edouard Oyallon, and Ga\u00ebl Varoquaux. Why do tree-based models still outperform deep learning on typical tabular data? Advances in neural information processing systems, 35:507--520, 2022."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00100"},{"key":"e_1_3_2_1_6_1","volume-title":"Roy Ka-Wei Lee, and Kwan Hui Lim. Btrec: Bert-based trajectory recommendation for personalized tours. arXiv preprint arXiv:2310.19886","author":"Ho Ngai Lam","year":"2023","unstructured":"Ngai Lam Ho, Roy Ka-Wei Lee, and Kwan Hui Lim. Btrec: Bert-based trajectory recommendation for personalized tours. arXiv preprint arXiv:2310.19886, 2023."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2023.104315"},{"key":"e_1_3_2_1_8_1","volume-title":"Time2vec: Learning a vector representation of time. arXiv preprint arXiv:1907.05321","author":"Kazemi Seyed Mehran","year":"2019","unstructured":"Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, and Marcus Brubaker. Time2vec: Learning a vector representation of time. arXiv preprint arXiv:1907.05321, 2019."},{"key":"e_1_3_2_1_9_1","volume-title":"A survey on deep learning for human mobility. ACM Computing Surveys (CSUR), 55(1):1--44","author":"Luca Massimiliano","year":"2021","unstructured":"Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, and Luca Pappalardo. A survey on deep learning for human mobility. ACM Computing Surveys (CSUR), 55(1):1--44, 2021."},{"key":"e_1_3_2_1_10_1","volume-title":"Anna Veronika Dorogush, and Andrey Gulin. Catboost: unbiased boosting with categorical features. Advances in neural information processing systems, 31","author":"Prokhorenkova Liudmila","year":"2018","unstructured":"Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, and Andrey Gulin. Catboost: unbiased boosting with categorical features. Advances in neural information processing systems, 31, 2018."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3349319"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.11.011"},{"key":"e_1_3_2_1_13_1","volume-title":"Scalable framework for enhancing raw gps trajectory data: application to trip analytics for transportation planning. Journal of big data analytics in transportation, 3(2):119--139","author":"Laan Zachary Vander","year":"2021","unstructured":"Zachary Vander Laan, Mark Franz, and Nikola Markovi\u0107. Scalable framework for enhancing raw gps trajectory data: application to trip analytics for transportation planning. Journal of big data analytics in transportation, 3(2):119--139, 2021."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00645"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-024-03237-9"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1140\/epjds\/s13688-020-00255-6"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011294"}],"event":{"name":"SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"],"location":"Atlanta GA USA","acronym":"SIGSPATIAL '24"},"container-title":["Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Human Mobility Prediction Challenge"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3681771.3699917","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3681771.3699917","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T15:29:09Z","timestamp":1759937349000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3681771.3699917"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,29]]},"references-count":17,"alternative-id":["10.1145\/3681771.3699917","10.1145\/3681771"],"URL":"https:\/\/doi.org\/10.1145\/3681771.3699917","relation":{},"subject":[],"published":{"date-parts":[[2024,10,29]]},"assertion":[{"value":"2024-12-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}