{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T20:40:57Z","timestamp":1742935257628,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319210414"},{"type":"electronic","value":"9783319210421"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-21042-1_23","type":"book-chapter","created":{"date-parts":[[2015,6,5]],"date-time":"2015-06-05T14:12:18Z","timestamp":1433513538000},"page":"285-296","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Mining Dependencies Considering Time Lag in Spatio-Temporal Traffic Data"],"prefix":"10.1007","author":[{"given":"Xiabing","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Haikun","family":"Hong","sequence":"additional","affiliation":[]},{"given":"Xingxing","family":"Xing","sequence":"additional","affiliation":[]},{"given":"Wenhao","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Kaigui","family":"Bian","sequence":"additional","affiliation":[]},{"given":"Kunqing","family":"Xie","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,6,6]]},"reference":[{"key":"23_CR1","doi-asserted-by":"crossref","unstructured":"Moneta, A., Spirtes, P.: Graphical models for the identification of causal structures in multivariate time series models. In: JCIS (2006)","DOI":"10.2991\/jcis.2006.171"},{"key":"23_CR2","unstructured":"Friedman, N., Nachman, I., Per, D.: Learning bayesian network structure from massive datasets: the \u201csparse candidate\u201d algorithm. In: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp. 206\u2013215 (1999)"},{"key":"23_CR3","first-page":"191","volume":"7","author":"R Silva","year":"2006","unstructured":"Silva, R., Scheines, R., Glymour, C., Spirtes, P.: Learning the structure of linear latent variable models. The Journal of Machine Learning Research 7, 191\u2013246 (2006)","journal-title":"The Journal of Machine Learning Research"},{"key":"23_CR4","doi-asserted-by":"crossref","unstructured":"Spirtes, P., Glymour, C.N., Scheines, R.: Causation, prediction, and search, vol. 81. MIT press (2000)","DOI":"10.7551\/mitpress\/1754.001.0001"},{"issue":"2","key":"23_CR5","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/atr.117","volume":"45","author":"S Lee","year":"2011","unstructured":"Lee, S., Heydecker, B., Kim, Y.H., Shon, E.-Y.: Dynamic od estimation using three phase traffic flow theory. Journal of Advanced Transportation 45(2), 143\u2013158 (2011)","journal-title":"Journal of Advanced Transportation"},{"key":"23_CR6","unstructured":"Barcel\u00f3, J., Montero, L., Bullejos, M., Serch, O., Carmona, C.: A kalman filter approach for the estimation of time dependent od matrices exploiting bluetooth traffic data collection. In: Transportation Research Board 91st Annual Meeting, number 12\u20133843 (2012)"},{"issue":"2","key":"23_CR7","first-page":"94","volume":"5","author":"H Zhao-cheng","year":"2005","unstructured":"Zhao-cheng, H., Zhi, Y.: Dynamic od estimation model of urban network [j]. Journal of Traffic and Transportation Engineering 5(2), 94\u201398 (2005)","journal-title":"Journal of Traffic and Transportation Engineering"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Han, L., Song, G., Cong, G., Xie, K.: Overlapping decomposition for causal graphical modeling. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012, pp. 114\u2013122 (2012)","DOI":"10.1145\/2339530.2339551"},{"key":"23_CR9","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/0165-1889(80)90069-X","volume":"2","author":"CWJ Granger","year":"1980","unstructured":"Granger, C.W.J.: Testing for causality: a personal viewpoint. Journal of Economic Dynamics and control 2, 329\u2013352 (1980)","journal-title":"Journal of Economic Dynamics and control"},{"key":"23_CR10","doi-asserted-by":"crossref","unstructured":"Yuan, M., Lin, Y.: Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society. Series B (Statistical Methodology) 68(1) (2006)","DOI":"10.1111\/j.1467-9868.2005.00532.x"},{"issue":"491","key":"23_CR11","doi-asserted-by":"publisher","first-page":"1202","DOI":"10.1198\/jasa.2010.tm08177","volume":"105","author":"F Li","year":"2010","unstructured":"Li, F., Zhang, N.R.: Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics. Journal of the American Statistical Association 105(491), 1202\u20131214 (2010)","journal-title":"Journal of the American Statistical Association"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Bahadori, M.T., Liu, Y.: Granger causality analysis in irregular time series. In: SDM, pp. 660\u2013671 (2012)","DOI":"10.1137\/1.9781611972825.57"},{"issue":"1","key":"23_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"AP Dempster","year":"1977","unstructured":"Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society, Series B 39(1), 1\u201338 (1977)","journal-title":"Journal of the Royal Statistical Society, Series B"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Meinshausen, N., B\u00fchlmann, P.: High-dimensional graphs and variable selection with the lasso. The Annals of Statistics, 1436\u20131462 (2006)","DOI":"10.1214\/009053606000000281"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Gao, Y., Sun, S.: Multi-link traffic flow forecasting using neural networks. In: 2010 Sixth International Conference on Natural Computation (ICNC), vol. 1, pp. 398\u2013401 (2010)","DOI":"10.1109\/ICNC.2010.5582914"},{"issue":"11","key":"23_CR16","doi-asserted-by":"publisher","first-page":"1358","DOI":"10.1061\/(ASCE)TE.1943-5436.0000435","volume":"138","author":"S Sun","year":"2012","unstructured":"Sun, S., Huang, R., Gao, Y.: Network-scale traffic modeling and forecasting with graphical lasso and neural networks. Journal of Transportation Engineering 138(11), 1358\u20131367 (2012)","journal-title":"Journal of Transportation Engineering"},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Kawale, J., Liess, S., Kumar, V., Lall, U., Ganguly, A.: Mining time-lagged relationships in spatio-temporal climate data. In: 2012 Conference on Intelligent Data Understanding (CIDU), pp. 130\u2013135 (2012)","DOI":"10.1109\/CIDU.2012.6382194"},{"key":"23_CR18","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.trc.2012.08.005","volume":"26","author":"S Yang","year":"2013","unstructured":"Yang, S.: On feature selection for traffic congestion prediction. Transportation Research Part C: Emerging Technologies 26, 160\u2013169 (2013)","journal-title":"Transportation Research Part C: Emerging Technologies"},{"key":"23_CR19","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58, 267\u2013288 (1996)","journal-title":"Journal of the Royal Statistical Society. Series B (Methodological)"},{"key":"23_CR20","unstructured":"Zhao, P., Rocha, G., Yu, B.: Grouped and hierarchical model selection through composite absolute penalties. Department of Statistics, UC Berkeley. Tech. Rep, 703 (2006)"},{"issue":"1","key":"23_CR21","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1080\/00031305.1992.10475841","volume":"46","author":"BC Arnold","year":"1992","unstructured":"Arnold, B.C., Brockett, P.L.: On distributions whose component ratios are cauchy. The American Statistician 46(1), 25\u201326 (1992)","journal-title":"The American Statistician"},{"key":"23_CR22","unstructured":"Carvalho, C.M., Polson, N.G., Scott, J.G.: Handling sparsity via the horseshoe. In: International Conference on Artificial Intelligence and Statistics, pp. 73\u201380 (2009)"},{"issue":"1","key":"23_CR23","first-page":"1891","volume":"14","author":"D Hern\u00e1ndez-Lobato","year":"2013","unstructured":"Hern\u00e1ndez-Lobato, D., Hern\u00e1ndez-Lobato, J.M., Dupont, P.: Generalized spike-and-slab priors for bayesian group feature selection using expectation propagation. The Journal of Machine Learning Research 14(1), 1891\u20131945 (2013)","journal-title":"The Journal of Machine Learning Research"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Qi, Y.A., Minka, T.P., Picard, R.W., Ghahramani, Z.: Predictive automatic relevance determination by expectation propagation. In: Proceedings of the Twenty-first International Conference on Machine Learning, ICML 2004, pp. 85\u201392 (2004)","DOI":"10.1145\/1015330.1015418"},{"issue":"1","key":"23_CR25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10618600.2000.10474858","volume":"9","author":"K Lange","year":"2000","unstructured":"Lange, K., Hunter, D.R., Yang, I.: Optimization transfer using surrogate objective functions. Journal of Computational and Graphical Statistics 9(1), 1\u201320 (2000)","journal-title":"Journal of Computational and Graphical Statistics"},{"issue":"5\u20136","key":"23_CR26","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1007\/s00041-008-9045-x","volume":"14","author":"EJ Candes","year":"2008","unstructured":"Candes, E.J., Wakin, M.B., Boyd, S.P.: Enhancing sparsity by reweighted $$\\ell _1$$ minimization. Journal of Fourier analysis and applications 14(5\u20136), 877\u2013905 (2008)","journal-title":"Journal of Fourier analysis and applications"},{"issue":"2","key":"23_CR27","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1109\/JSTSP.2010.2042413","volume":"4","author":"D Wipf","year":"2010","unstructured":"Wipf, D., Nagarajan, S.: Iterative reweighted $$\\ell _{1}$$ and $$\\ell _{2}$$ methods for finding sparse solutions. IEEE Journal of Selected Topics in Signal Processing 4(2), 317\u2013329 (2010)","journal-title":"IEEE Journal of Selected Topics in Signal Processing"},{"key":"23_CR28","doi-asserted-by":"crossref","unstructured":"Arnold, A., Liu, Y., Abe, N.: Temporal causal modeling with graphical granger methods. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007, pp. 66\u201375 (2007)","DOI":"10.1145\/1281192.1281203"},{"issue":"1","key":"23_CR29","first-page":"64","volume":"46","author":"S Meng","year":"2010","unstructured":"Meng, S., Lei, H., Kunqing, X., Guojie, S., Xiujun, M., Guanhua, C.: An adaptive traffic flow prediction mechanism based on locally weighted learning. Acta Scientiarum Naturalium Universitatis Pekinensis 46(1), 64\u201368 (2010)","journal-title":"Acta Scientiarum Naturalium Universitatis Pekinensis"}],"container-title":["Lecture Notes in Computer Science","Web-Age Information Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-21042-1_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,9]],"date-time":"2024-06-09T10:52:11Z","timestamp":1717930331000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-21042-1_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319210414","9783319210421"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-21042-1_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"6 June 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}