{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:58:01Z","timestamp":1740099481930,"version":"3.37.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030298937"},{"type":"electronic","value":"9783030298944"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-29894-4_26","type":"book-chapter","created":{"date-parts":[[2019,8,22]],"date-time":"2019-08-22T17:41:59Z","timestamp":1566495719000},"page":"307-321","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Detection of Anomalous Traffic Patterns and Insight Analysis from Bus Trajectory Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3783-6560","authenticated-orcid":false,"given":"Xiaocai","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Xuan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Sunny","family":"Verma","sequence":"additional","affiliation":[]},{"given":"Yuansheng","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Michael","family":"Blumenstein","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1833-7413","authenticated-orcid":false,"given":"Jinyan","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,23]]},"reference":[{"key":"26_CR1","unstructured":"Guiyang open government data platform. \n                      http:\/\/www.gyopendata.gov.cn\/city\/index.htm\n                      \n                    . Accessed 1 Feb 2018"},{"issue":"3","key":"26_CR2","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. ACM Comput. Surv. (CSUR) 41(3), 15 (2009)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Chawla, S., Zheng, Y., Hu, J.: Inferring the root cause in road traffic anomalies. In: Proceedings of 2012 IEEE 12th International Conference on Data Mining, pp. 141\u2013150 (2012)","DOI":"10.1109\/ICDM.2012.104"},{"key":"26_CR4","first-page":"1263","volume":"9","author":"H He","year":"2008","unstructured":"He, H., Garcia, E.A.: Learning from imbalanced data. IEEE Trans. Knowl. Data Eng. 9, 1263\u20131284 (2008)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Juvonen, A., Hamalainen, T.: An efficient network log anomaly detection system using random projection dimensionality reduction. In: Proceedings of 2014 6th International Conference on New Technologies, Mobility and Security (NTMS), pp. 1\u20135. IEEE (2014)","DOI":"10.1109\/NTMS.2014.6814006"},{"issue":"3","key":"26_CR6","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1007\/s11280-017-0487-4","volume":"21","author":"X Kong","year":"2018","unstructured":"Kong, X., Song, X., Xia, F., Guo, H., Wang, J., Tolba, A.: LoTAD: long-term traffic anomaly detection based on crowdsourced bus trajectory data. World Wide Web 21(3), 825\u2013847 (2018)","journal-title":"World Wide Web"},{"key":"26_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/809582","volume":"2015","author":"W Kuang","year":"2015","unstructured":"Kuang, W., An, S., Jiang, H.: Detecting traffic anomalies in urban areas using taxi GPS data. Math. Probl. Eng. 2015, 1\u201314 (2015)","journal-title":"Math. Probl. Eng."},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Lakhina, A., Crovella, M., Diot, C.: Diagnosing network-wide traffic anomalies. In: ACM SIGCOMM Computer Communication Review, vol. 34, pp. 219\u2013230. ACM (2004)","DOI":"10.1145\/1030194.1015492"},{"key":"26_CR9","unstructured":"Li, K.L., Huang, H.K., Tian, S.F., Xu, W.: Improving one-class SVM for anomaly detection. In: Proceedings of 2003 International Conference on Machine Learning Cybernetics, vol. 5, pp. 3077\u20133081. IEEE (2003)"},{"key":"26_CR10","doi-asserted-by":"publisher","first-page":"40281","DOI":"10.1109\/ACCESS.2018.2851747","volume":"6","author":"Y Li","year":"2018","unstructured":"Li, Y., Guo, T., Xia, R., Xie, W.: Road traffic anomaly detection based on fuzzy theory. IEEE Access 6, 40281\u201340288 (2018)","journal-title":"IEEE Access"},{"issue":"5","key":"26_CR11","doi-asserted-by":"publisher","first-page":"2487","DOI":"10.1007\/s11042-015-2637-y","volume":"75","author":"Y Li","year":"2016","unstructured":"Li, Y., Liu, W., Huang, Q.: Traffic anomaly detection based on image descriptor in videos. Multimedia Tools Appl. 75(5), 2487\u20132505 (2016)","journal-title":"Multimedia Tools Appl."},{"issue":"9","key":"26_CR12","doi-asserted-by":"publisher","first-page":"2477","DOI":"10.1109\/TITS.2017.2649541","volume":"18","author":"H Liu","year":"2017","unstructured":"Liu, H., Taniguchi, T., Tanaka, Y., Takenaka, K., Bando, T.: Visualization of driving behavior based on hidden feature extraction by using deep learning. IEEE Trans. Intell. Transp. Syst. 18(9), 2477\u20132489 (2017)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Liu, W., Zheng, Y., Chawla, S., Yuan, J., Xing, X.: Discovering spatio-temporal causal interactions in traffic data streams. In: Proc. 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1010\u20131018. ACM (2011)","DOI":"10.1145\/2020408.2020571"},{"key":"26_CR14","unstructured":"M\u00fcnz, G., Li, S., Carle, G.: Traffic anomaly detection using k-means clustering. In: GI\/ITG Workshop MMBnet, pp. 13\u201314 (2007)"},{"key":"26_CR15","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1007\/978-3-319-31753-3_43","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"H Nguyen","year":"2016","unstructured":"Nguyen, H., Liu, W., Rivera, P., Chen, F.: TrafficWatch: real-time traffic incident detection and monitoring using social media. In: Bailey, J., Khan, L., Washio, T., Dobbie, G., Huang, J.Z., Wang, R. (eds.) PAKDD 2016. LNCS (LNAI), vol. 9651, pp. 540\u2013551. Springer, Cham (2016). \n                      https:\/\/doi.org\/10.1007\/978-3-319-31753-3_43"},{"key":"26_CR16","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.datak.2013.05.002","volume":"87","author":"L Pang","year":"2013","unstructured":"Pang, L., Chawla, S., Liu, W., Zheng, Y.: On detection of emerging anomalous traffic patterns using GPS data. Data Knowl. Eng. 87, 357\u2013373 (2013)","journal-title":"Data Knowl. Eng."},{"issue":"8","key":"26_CR17","doi-asserted-by":"publisher","first-page":"2260","DOI":"10.1109\/TITS.2017.2675710","volume":"18","author":"M Riveiro","year":"2017","unstructured":"Riveiro, M., Lebram, M., Elmer, M.: Anomaly detection for road traffic: a visual analytics framework. IEEE Trans. Intell. Transp. Syst. 18(8), 2260\u20132270 (2017)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"1","key":"26_CR18","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.patcog.2009.05.017","volume":"43","author":"CF Tsai","year":"2010","unstructured":"Tsai, C.F., Lin, C.Y.: A triangle area based nearest neighbors approach to intrusion detection. Pattern Recogn. 43(1), 222\u2013229 (2010)","journal-title":"Pattern Recogn."},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, D., Li, N., Zhou, Z.H., Chen, C., Sun, L., Li, S.: iBAT: detecting anomalous taxi trajectories from GPS traces. In: Proceedings of 13th International Conference on Ubiquitous Computing, pp. 99\u2013108. ACM (2011)","DOI":"10.1145\/2030112.2030127"},{"key":"26_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, X., Zhao, Z., Zheng, Y., Li, J.: Prediction of taxi destinations using a novel data embedding method and ensemble learning. IEEE Trans. Intell. Transp. Syst 1\u201311 (2019). \n                      https:\/\/doi.org\/10.1109\/TITS.2018.2888587","DOI":"10.1109\/TITS.2018.2888587"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2019: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29894-4_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,22]],"date-time":"2019-08-22T17:46:15Z","timestamp":1566495975000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-29894-4_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030298937","9783030298944"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29894-4_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cuvu, Yanuka Island","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Fiji","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pricai.org\/2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}