{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T15:45:07Z","timestamp":1767973507054,"version":"3.49.0"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T00:00:00Z","timestamp":1693958400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T00:00:00Z","timestamp":1693958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100010666","name":"H2020 Research Infrastructures","doi-asserted-by":"publisher","award":["871042"],"award-info":[{"award-number":["871042"]}],"id":[{"id":"10.13039\/100010666","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Piano Nazionale di Ripresa e Resilienza","award":["prot. IR0000013"],"award-info":[{"award-number":["prot. IR0000013"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1007\/s10994-023-06386-x","type":"journal-article","created":{"date-parts":[[2023,9,6]],"date-time":"2023-09-06T19:01:28Z","timestamp":1694026888000},"page":"4597-4634","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Trajectory test-train overlap in next-location prediction datasets"],"prefix":"10.1007","volume":"112","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6964-9877","authenticated-orcid":false,"given":"Massimiliano","family":"Luca","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Pappalardo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruno","family":"Lepri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gianni","family":"Barlacchi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,6]]},"reference":[{"key":"6386_CR1","doi-asserted-by":"crossref","unstructured":"Amichi, L., Viana, A. C., Crovella, M., & Loureiro, A. A. (2020). Understanding individuals\u2019 proclivity for novelty seeking. In Proceedings of the 28th international conference on advances in geographic information systems (pp. 314\u2013324).","DOI":"10.1145\/3397536.3422248"},{"key":"6386_CR2","unstructured":"Arora, N., Cabannes, T., Ganapathy, S.V., Li, Y., Mcafee, P., Nunkesser, M., Osorio, C., Tomkins, A., & Tsogsuren, I. (2021). Quantifying the sustainability impact of google maps: A case study of salt lake city. arXiv:2111.03426"},{"key":"6386_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.physrep.2018.01.001","volume":"734","author":"H Barbosa","year":"2018","unstructured":"Barbosa, H., Barthelemy, M., Ghoshal, G., James, C. R., Lenormand, M., Louail, T., Menezes, R., Ramasco, J. J., Simini, F., & Tomasini, M. (2018). Human mobility: Models and applications. Physics Reports, 734, 1\u201374.","journal-title":"Physics Reports"},{"key":"6386_CR4","first-page":"1","volume":"27","author":"G Barlacchi","year":"2017","unstructured":"Barlacchi, G., Perentis, C., Mehrotra, A., Musolesi, M., & Lepri, B. (2017). Are you getting sick? Predicting influenza-like symptoms using human mobility behaviors. EPJ Data Science, 27, 1\u201315.","journal-title":"EPJ Data Science"},{"issue":"3","key":"6386_CR5","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1002\/sd.1582","volume":"23","author":"L Blanc","year":"2015","unstructured":"Blanc, L. (2015). David: Towards integration at last? The sustainable development goals as a network of targets. Sustainable Development, 23(3), 176\u2013187. https:\/\/doi.org\/10.1002\/sd.1582","journal-title":"Sustainable Development"},{"issue":"8","key":"6386_CR6","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1038\/s41893-022-00903-x","volume":"5","author":"M B\u00f6hm","year":"2022","unstructured":"B\u00f6hm, M., Nanni, M., & Pappalardo, L. (2022). Gross polluters and vehicle emissions reduction. Nature Sustainability, 5(8), 699\u2013707.","journal-title":"Nature Sustainability"},{"key":"6386_CR7","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1108\/17427371211221063","volume":"8","author":"I Burbey","year":"2012","unstructured":"Burbey, I., & Martin, T. L. (2012). A survey on predicting personal mobility. International Journal of Pervasive Computing and Communications, 8, 5\u201322.","journal-title":"International Journal of Pervasive Computing and Communications"},{"key":"6386_CR8","doi-asserted-by":"crossref","unstructured":"Calabrese, F., Di\u00a0Lorenzo, G., & Ratti, C. (2010). Human mobility prediction based on individual and collective geographical preferences. In 13th International IEEE conference on intelligent transportation systems (pp. 312\u2013317).","DOI":"10.1109\/ITSC.2010.5625119"},{"key":"6386_CR9","doi-asserted-by":"crossref","unstructured":"Canzian, L., & Musolesi, M. (2015). Trajectories of depression: Unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing (pp. 1293\u20131304).","DOI":"10.1145\/2750858.2805845"},{"key":"6386_CR10","unstructured":"Chang, S., Zhang, Y., Han, W., Yu, M., Guo, X., Tan, W., Cui, X., Witbrock, M., Hasegawa-Johnson, M. A., & Huang, T. S. (2017). Dilated recurrent neural networks. Advances in Neural Information Processing Systems, 30."},{"key":"6386_CR11","doi-asserted-by":"crossref","unstructured":"Cho, E., Myers, S. A., Leskovec, J. (2011). Friendship and mobility: User movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1082\u20131090).","DOI":"10.1145\/2020408.2020579"},{"key":"6386_CR12","doi-asserted-by":"crossref","unstructured":"Comito, C. (2017). Where are you going? next place prediction from twitter. In 2017 IEEE international conference on data science and advanced analytics (DSAA) (pp. 696\u2013705). IEEE.","DOI":"10.1109\/DSAA.2017.56"},{"key":"6386_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106205","volume":"204","author":"C Comito","year":"2020","unstructured":"Comito, C. (2020). Next: A framework for next-place prediction on location based social networks. Knowledge-Based Systems, 204, 106205.","journal-title":"Knowledge-Based Systems"},{"key":"6386_CR14","doi-asserted-by":"publisher","unstructured":"Cornacchia, G., B\u00f6hm, M., Mauro, G., Nanni, M., Pedreschi, D., & Pappalardo, L. (2022). How routing strategies impact urban emissions. In Proceedings of the 30th international conference on advances in geographic information systems. SIGSPATIAL \u201922. Association for Computing Machinery. https:\/\/doi.org\/10.1145\/3557915.3560977","DOI":"10.1145\/3557915.3560977"},{"issue":"1","key":"6386_CR15","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1140\/epjds\/s13688-021-00304-8","volume":"10","author":"D do Couto Teixeira","year":"2021","unstructured":"do Couto Teixeira, D., Almeida, J. M., & Viana, A. C. (2021). On estimating the predictability of human mobility: The role of routine. EPJ Data Science, 10(1), 49.","journal-title":"EPJ Data Science"},{"key":"6386_CR16","doi-asserted-by":"crossref","unstructured":"Feng, J., Li, Y., Zhang, C., Sun, F., Meng, F., Guo, A., & Jin, D. (2018). Deepmove: Predicting human mobility with attentional recurrent networks. In Proceedings of the 2018 world wide web conference (pp. 1459\u20131468).","DOI":"10.1145\/3178876.3186058"},{"key":"6386_CR17","doi-asserted-by":"crossref","unstructured":"Gambs, S., Killijian, M.-O., & del Prado\u00a0Cortez, M. N. (2010). Show me how you move and i will tell you who you are. In Proceedings of the 3rd ACM SIGSPATIAL international workshop on security and privacy in GIS and LBS (pp. 34\u201341).","DOI":"10.1145\/1868470.1868479"},{"key":"6386_CR18","doi-asserted-by":"crossref","unstructured":"Gambs, S., Killijian, M.-O., & del Prado\u00a0Cortez, M. N. (2012). Next place prediction using mobility Markov chains. In Proceedings of the first workshop on measurement, privacy, and mobility (pp. 1\u20136).","DOI":"10.1145\/2181196.2181199"},{"key":"6386_CR19","doi-asserted-by":"crossref","unstructured":"Gao, Q., Zhou, F., Trajcevski, G., Zhang, K., Zhong, T., & Zhang, F. (2019). Predicting human mobility via variational attention. In The world wide web conference (pp. 2750\u20132756).","DOI":"10.1145\/3308558.3313610"},{"issue":"6324","key":"6386_CR20","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1126\/science.aal3856","volume":"355","author":"JM Hofman","year":"2017","unstructured":"Hofman, J. M., Sharma, A., & Watts, D. J. (2017). Prediction and explanation in social systems. Science, 355(6324), 486\u2013488.","journal-title":"Science"},{"key":"6386_CR21","unstructured":"Kawaguchi, K., Kaelbling, L. P., & Bengio, Y. (2017). Generalization in deep learning. arXiv preprint arXiv:1710.05468"},{"key":"6386_CR22","doi-asserted-by":"publisher","first-page":"171528","DOI":"10.1109\/ACCESS.2020.3024979","volume":"8","author":"L Khaidem","year":"2020","unstructured":"Khaidem, L., Luca, M., Yang, F., Anand, A., Lepri, B., & Dong, W. (2020). Optimizing transportation dynamics at a city-scale using a reinforcement learning framework. IEEE Access, 8, 171528\u2013171541.","journal-title":"IEEE Access"},{"key":"6386_CR23","unstructured":"Kingma, D. P., & Ba, J. (2014). Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"6386_CR24","doi-asserted-by":"crossref","unstructured":"Kong, D., & Wu, F. (2018). Hst-lstm: A hierarchical spatial-temporal long-short term memory network for location prediction. In IJCAI (pp. 2341\u20132347).","DOI":"10.24963\/ijcai.2018\/324"},{"issue":"1","key":"6386_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1057\/s41599-019-0335-5","volume":"5","author":"C Kroll","year":"2019","unstructured":"Kroll, C., Warchold, A., & Pradhan, P. (2019). Sustainable development goals (SDGS): Are we successful in turning trade-offs into synergies? Palgrave Communications, 5(1), 1\u201311. https:\/\/doi.org\/10.1057\/s41599-019-0335-5","journal-title":"Palgrave Communications"},{"issue":"4","key":"6386_CR26","doi-asserted-by":"publisher","first-page":"432","DOI":"10.3390\/e21040432","volume":"21","author":"V Kulkarni","year":"2019","unstructured":"Kulkarni, V., Mahalunkar, A., Garbinato, B., & Kelleher, J. D. (2019). Examining the limits of predictability of human mobility. Entropy, 21(4), 432.","journal-title":"Entropy"},{"key":"6386_CR27","doi-asserted-by":"crossref","unstructured":"Lewis, P., Stenetorp, P., & Riedel, S. (2020). Question and answer test-train overlap in open-domain question answering datasets. arXiv preprint arXiv:2008.02637.","DOI":"10.18653\/v1\/2021.eacl-main.86"},{"key":"6386_CR28","unstructured":"Liu, L., Lewis, P., Riedel, S., & Stenetorp, P. (2012). Challenges in generalization in open domain question answeringx."},{"key":"6386_CR29","doi-asserted-by":"crossref","unstructured":"Liu, Q., Wu, S., Wang, L., & Tan, T. (2016). Predicting the next location: A recurrent model with spatial and temporal contexts. In Thirtieth AAAI conference on artificial intelligence.","DOI":"10.1609\/aaai.v30i1.9971"},{"issue":"1","key":"6386_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3485125","volume":"55","author":"M Luca","year":"2021","unstructured":"Luca, M., Barlacchi, G., Lepri, B., & Pappalardo, L. (2021). A survey on deep learning for human mobility. ACM Computing Surveys, 55(1), 1\u201344. https:\/\/doi.org\/10.1145\/3485125","journal-title":"ACM Computing Surveys"},{"key":"6386_CR31","doi-asserted-by":"crossref","unstructured":"Luo, Y., Liu, Q., & Liu, Z. (2021). Stan: Spatio-temporal attention network for next location recommendation. In Proceedings of the web conference 2021 (pp. 2177\u20132185).","DOI":"10.1145\/3442381.3449998"},{"issue":"3","key":"6386_CR32","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1109\/TITS.2013.2262376","volume":"14","author":"L Moreira-Matias","year":"2013","unstructured":"Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., & Damas, L. (2013). Predicting taxi-passenger demand using streaming data. IEEE Transactions on Intelligent Transportation Systems, 14(3), 1393\u20131402.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"6386_CR33","doi-asserted-by":"crossref","unstructured":"Pappalardo, L., Simini, F., Barlacchi, G., & Pellungrini, R. (2022). Scikit-mobility: A Python library for the analysis, generation, and risk assessment of mobility data. Journal of Statistical Software, 103(4), 1\u201338.https:\/\/doi.org\/10.18637\/jss.v103.i04","DOI":"10.18637\/jss.v103.i04"},{"issue":"1","key":"6386_CR34","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1038\/s41597-022-01893-3","volume":"10","author":"L Pappalardo","year":"2023","unstructured":"Pappalardo, L., Cornacchia, G., Navarro, V., Bravo, L., & Ferres, L. (2023). A dataset to assess mobility changes in Chile following local quarantines. Scientific Data, 10(1), 6.","journal-title":"Scientific Data"},{"issue":"1","key":"6386_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/ncomms9166","volume":"6","author":"L Pappalardo","year":"2015","unstructured":"Pappalardo, L., Simini, F., Rinzivillo, S., Pedreschi, D., Giannotti, F., & Barab\u00e1si, A.-L. (2015). Returners and explorers dichotomy in human mobility. Nature Communications, 6(1), 1\u20138.","journal-title":"Nature Communications"},{"key":"6386_CR36","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/s41060-016-0013-2","volume":"2","author":"L Pappalardo","year":"2016","unstructured":"Pappalardo, L., Vanhoof, M., Gabrielli, L., Smoreda, Z., Pedreschi, D., & Giannotti, F. (2016). An analytical framework to nowcast well-being using mobile phone data. International Journal of Data Science and Analytics, 2, 75\u201392.","journal-title":"International Journal of Data Science and Analytics"},{"key":"6386_CR37","doi-asserted-by":"publisher","unstructured":"Piorkowski, M., Sarafijanovic-Djukic, N., & Grossglauser, M. (2009). CRAWDAD dataset epfl\/mobility (v. 2009-02-24). Downloaded from https:\/\/doi.org\/10.15783\/C7J010","DOI":"10.15783\/C7J010"},{"key":"6386_CR38","first-page":"318","volume-title":"Learning internal representations by error propagation","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by error propagation (pp. 318\u2013362). MIT Press."},{"issue":"7860","key":"6386_CR39","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1038\/s41586-021-03480-9","volume":"593","author":"M Schl\u00e4pfer","year":"2021","unstructured":"Schl\u00e4pfer, M., Dong, L., O\u2019Keeffe, K., Santi, P., Szell, M., Salat, H., Anklesaria, S., Vazifeh, M., Ratti, C., & West, G. B. (2021). The universal visitation law of human mobility. Nature, 593(7860), 522\u2013527.","journal-title":"Nature"},{"key":"6386_CR40","doi-asserted-by":"crossref","unstructured":"Sen, P., & Saffari, A. (2020). What do models learn from question answering datasets? arXiv preprint arXiv:2004.03490","DOI":"10.18653\/v1\/2020.emnlp-main.190"},{"key":"6386_CR41","doi-asserted-by":"crossref","unstructured":"Shi, Y., Feng, H., Geng, X., Tang, X., & Wang, Y. (2019). A survey of hybrid deep learning methods for traffic flow prediction. In Proceedings of the 2019 3rd international conference on advances in image processing (pp. 133\u2013138).","DOI":"10.1145\/3373419.3373429"},{"issue":"1","key":"6386_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-021-94102-x","volume":"11","author":"K Smolak","year":"2021","unstructured":"Smolak, K., Si\u0142a-Nowicka, K., Delvenne, J.-C., Wierzbi\u0144ski, M., & Rohm, W. (2021). The impact of human mobility data scales and processing on movement predictability. Scientific Reports, 11(1), 1\u201310.","journal-title":"Scientific Reports"},{"key":"6386_CR43","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1126\/science.1177170","volume":"327","author":"C Song","year":"2010","unstructured":"Song, C., Qu, Z., Blumm, N., & Barab\u00e1si, A.-L. (2010). Limits of predictability in human mobility. Science, 327, 1018\u20131021.","journal-title":"Science"},{"key":"6386_CR44","doi-asserted-by":"crossref","unstructured":"Sun, K., Qian, T., Chen, T., Liang, Y., Nguyen, Q. V. H., & Yin, H. (2020). Where to go next: Modeling long-and short-term user preferences for point-of-interest recommendation. In Proceedings of the AAAI conference on artificial intelligence (Vol. 34, pp. 214\u2013221).","DOI":"10.1609\/aaai.v34i01.5353"},{"key":"6386_CR45","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1016\/j.is.2015.11.002","volume":"64","author":"R Trasarti","year":"2017","unstructured":"Trasarti, R., Guidotti, R., Monreale, A., & Giannotti, F. (2017). Myway: Location prediction via mobility profiling. Information Systems, 64, 350\u2013367.","journal-title":"Information Systems"},{"key":"6386_CR46","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s41060-020-00224-2","volume":"11","author":"V Voukelatou","year":"2020","unstructured":"Voukelatou, V., Gabrielli, L., Miliou, I., Cresci, S., Sharma, R., Tesconi, M., & Pappalardo, L. (2020). Measuring objective and subjective well-being: Dimensions and data sources. International Journal of Data Science and Analytics, 11, 279\u2013309.","journal-title":"International Journal of Data Science and Analytics"},{"key":"6386_CR47","doi-asserted-by":"crossref","unstructured":"Wang, X., Girshick, R., Gupta, A., & He, K. (2018). Non-local neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 7794\u20137803).","DOI":"10.1109\/CVPR.2018.00813"},{"key":"6386_CR48","doi-asserted-by":"publisher","unstructured":"Wang, J., Jiang, J., Jiang, W., Li, C., & Zhao, W. X. (2021). Libcity: An open library for traffic prediction. In Proceedings of the 29th international conference on advances in geographic information systems. (SIGSPATIAL \u201921, pp. 145\u2013148). Association for Computing Machinery. https:\/\/doi.org\/10.1145\/3474717.3483923","DOI":"10.1145\/3474717.3483923"},{"issue":"3","key":"6386_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3386252","volume":"53","author":"Y Wang","year":"2020","unstructured":"Wang, Y., Yao, Q., Kwok, J. T., & Ni, L. M. (2020). Generalizing from a few examples: A survey on few-shot learning. ACM Computing Surveys (CSUR), 53(3), 1\u201334.","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"6386_CR50","doi-asserted-by":"publisher","first-page":"108","DOI":"10.26599\/BDMA.2018.9020010","volume":"1","author":"R Wu","year":"2018","unstructured":"Wu, R., Luo, G., Shao, J., Tian, L., & Peng, C. (2018). Location prediction on trajectory data: A review. Big Data Mining and Analytics, 1, 108\u2013127.","journal-title":"Big Data Mining and Analytics"},{"key":"6386_CR51","doi-asserted-by":"crossref","unstructured":"Yang, D., Fankhauser, B., Rosso, P., & Cudre-Mauroux, P. (2020). Location prediction over sparse user mobility traces using RNNS: Flashback in hidden states! In Proceedings of the twenty-ninth international joint conference on artificial intelligence (IJCAI-20, pp. 2184\u20132190).","DOI":"10.24963\/ijcai.2020\/302"},{"issue":"1","key":"6386_CR52","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TSMC.2014.2327053","volume":"45","author":"D Yang","year":"2014","unstructured":"Yang, D., Zhang, D., Zheng, V. W., & Yu, Z. (2014). Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNS. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(1), 129\u2013142.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"6386_CR53","doi-asserted-by":"crossref","unstructured":"Yao, D., Zhang, C., Huang, J., & Bi, J. (2017). Serm: A recurrent model for next location prediction in semantic trajectories. In Proceedings of the 2017 ACM on conference on information and knowledge management (pp. 2411\u20132414).","DOI":"10.1145\/3132847.3133056"},{"key":"6386_CR54","first-page":"4514","volume":"35","author":"C Zhang","year":"2022","unstructured":"Zhang, C., Zhao, K., & Chen, M. (2022). Beyond the limits of predictability in human mobility prediction: Context-transition predictability. IEEE Transactions on Knowledge and Data Engineering, 35, 4514\u20134526.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"6386_CR55","doi-asserted-by":"crossref","unstructured":"Zhao, L. (2020). Event prediction in big data era: A systematic survey. arXiv preprint arXiv:2007.09815","DOI":"10.36227\/techrxiv.12733049"},{"issue":"9","key":"6386_CR56","doi-asserted-by":"publisher","first-page":"1652","DOI":"10.1109\/TKDE.2018.2807840","volume":"30","author":"X Zheng","year":"2018","unstructured":"Zheng, X., Han, J., & Sun, A. (2018). A survey of location prediction on twitter. IEEE Transactions on Knowledge and Data Engineering, 30(9), 1652\u20131671.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"6386_CR57","doi-asserted-by":"crossref","unstructured":"Zhou, K., Liu, Z., Qiao, Y., Xiang, T., & Loy, C. C. (2021). Domain generalization: A survey. arXiv preprint arXiv:2103.02503","DOI":"10.1109\/TPAMI.2022.3195549"},{"key":"6386_CR58","doi-asserted-by":"crossref","unstructured":"Zhu, W.-Y., Peng, W.-C., Chen, L.-J., Zheng, K., & Zhou, X. (2015). Modeling user mobility for location promotion in location-based social networks. In Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1573\u20131582).","DOI":"10.1145\/2783258.2783331"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-023-06386-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10994-023-06386-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-023-06386-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T00:03:09Z","timestamp":1725580989000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10994-023-06386-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,6]]},"references-count":58,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["6386"],"URL":"https:\/\/doi.org\/10.1007\/s10994-023-06386-x","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,6]]},"assertion":[{"value":"10 February 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}