{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T23:09:11Z","timestamp":1778368151915,"version":"3.51.4"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032191045","type":"print"},{"value":"9783032191052","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-19105-2_43","type":"book-chapter","created":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T22:18:28Z","timestamp":1778365108000},"page":"621-631","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Rotation- and\u00a0Scale-Invariant Shape Extraction from\u00a0Vessel Trajectories for\u00a0Human-in-The-Loop Monitoring: A\u00a0Case Study at\u00a0the\u00a0Ports of\u00a0Brittany"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4907-9728","authenticated-orcid":false,"given":"Cristiano","family":"Landi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3313-1560","authenticated-orcid":false,"given":"Natalia","family":"Andrienko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8574-6295","authenticated-orcid":false,"given":"Gennady","family":"Andrienko","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,5,1]]},"reference":[{"key":"43_CR1","doi-asserted-by":"publisher","unstructured":"Andrienko, N.V., Andrienko, G.L.: Visual analytics of vessel movement. In: Guide to Maritime Informatics, pp. 149\u2013170. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-61852-0_5","DOI":"10.1007\/978-3-030-61852-0_5"},{"issue":"3","key":"43_CR2","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/MCG.2024.3379851","volume":"44","author":"NV Andrienko","year":"2024","unstructured":"Andrienko, N.V., Andrienko, G.L., Artikis, A., Mantenoglou, P., Rinzivillo, S.: Human-in-the-loop: visual analytics for building models recognizing behavioral patterns in time series. IEEE Comput. Graphics Appl. 44(3), 14\u201329 (2024)","journal-title":"IEEE Comput. Graphics Appl."},{"key":"43_CR3","doi-asserted-by":"crossref","unstructured":"Ankerst, M., Breunig, M.M., Kriegel, H., Sander, J.: OPTICS: ordering points to identify the clustering structure. In: SIGMOD Conference, pp. 49\u201360. ACM Press (1999)","DOI":"10.1145\/304182.304187"},{"issue":"2","key":"43_CR4","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/0031-3203(81)90009-1","volume":"13","author":"DH Ballard","year":"1981","unstructured":"Ballard, D.H.: Generalizing the hough transform to detect arbitrary shapes. Pattern Recognit. 13(2), 111\u2013122 (1981)","journal-title":"Pattern Recognit."},{"issue":"4","key":"43_CR5","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1007\/PL00011461","volume":"2","author":"B Boots","year":"2000","unstructured":"Boots, B., Tiefelsdorf, M.: Global and local spatial autocorrelation in bounded regular tessellations. J. Geogr. Syst. 2(4), 319\u2013348 (2000)","journal-title":"J. Geogr. Syst."},{"key":"43_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ocecoaman.2021.106015","volume":"218","author":"H Duan","year":"2022","unstructured":"Duan, H., Ma, F., Miao, L., Zhang, C.: A semi-supervised deep learning approach for vessel trajectory classification based on ais data. Ocean Coast. Manage. 218, 106015 (2022). https:\/\/doi.org\/10.1016\/j.ocecoaman.2021.106015","journal-title":"Ocean Coast. Manage."},{"key":"43_CR7","doi-asserted-by":"publisher","unstructured":"Endo, Y., Toda, H., Nishida, K., Kawanobe, A.: Deep feature extraction from trajectories for transportation mode estimation. In: PAKDD (2). Lecture Notes in Computer Science, vol.\u00a09652, pp. 54\u201366. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-31750-2_5","DOI":"10.1007\/978-3-319-31750-2_5"},{"key":"43_CR8","unstructured":"Ester, M., Kriegel, H., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD. pp. 226\u2013231. AAAI Press (1996)"},{"key":"43_CR9","doi-asserted-by":"publisher","unstructured":"Han, F., Liu, Y., Tian, H., Li, J., Tian, Y.: A comprehensive framework incorporating deep learning for analyzing fishing vessel activity using automatic identification system data. ICES J. Mar. Sci. 82(2), fsae166 (2024). https:\/\/doi.org\/10.1093\/icesjms\/fsae166","DOI":"10.1093\/icesjms\/fsae166"},{"key":"43_CR10","doi-asserted-by":"crossref","unstructured":"Kontopoulos, I., Chatzikokolakis, K., Tserpes, K., Zissis, D.: Classification of vessel activity in streaming data. In: DEBS, pp. 153\u2013164. ACM (2020)","DOI":"10.1145\/3401025.3401763"},{"key":"43_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2023.101306","volume":"21","author":"I Kontopoulos","year":"2023","unstructured":"Kontopoulos, I., Makris, A., Tserpes, K.: Traclets: a trajectory representation and classification library. SoftwareX 21, 101306 (2023)","journal-title":"SoftwareX"},{"key":"43_CR12","doi-asserted-by":"crossref","unstructured":"Landi, C., Guidotti, R.: Shape-based methods in mobility data analysis: Effectiveness and limitations. GeoInformatica (2025), just Accepted","DOI":"10.21203\/rs.3.rs-5369626\/v1"},{"key":"43_CR13","doi-asserted-by":"crossref","unstructured":"Landi, C., Guidotti, R., Nanni, M., Monreale, A.: The trajectory interval forest classifier for trajectory classification. In: SIGSPATIAL\/GIS, pp. 67:1\u201367:4. ACM (2023)","DOI":"10.1145\/3589132.3625617"},{"key":"43_CR14","doi-asserted-by":"crossref","unstructured":"Landi, C., Spinnato, F., Guidotti, R., Monreale, A., Nanni, M.: Geolet: an interpretable model for trajectory classification. In: IDA. Lecture Notes in Computer Science, vol. 13876, pp. 236\u2013248. Springer (2023)","DOI":"10.1007\/978-3-031-30047-9_19"},{"issue":"4","key":"43_CR15","first-page":"1","volume":"5","author":"H Liu","year":"2021","unstructured":"Liu, H., Chen, X., Wang, Y., Zhang, B., Chen, Y., Zhao, Y., Zhou, F.: Visualization and visual analysis of vessel trajectory data: a survey. Vis. Inf. 5(4), 1\u201310 (2021)","journal-title":"Vis. Inf."},{"issue":"11","key":"43_CR16","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/joss.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes, L., Healy, J., Astels, S.: Hdbscan: aierarchical density based clustering. J. Open Source Softw. 2(11), 205 (2017)","journal-title":"J. Open Source Softw."},{"key":"43_CR17","doi-asserted-by":"publisher","unstructured":"Petry, L.M., J\u00fanior, A.S., Bogorny, V., Brandoli, B., Matwin, S.: Challenges in vessel behavior and anomaly detection: from classical machine learning to deep learning. In: Canadian AI. Lecture Notes in Computer Science, vol. 12109, pp. 401\u2013407. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-47358-7_41","DOI":"10.1007\/978-3-030-47358-7_41"},{"key":"43_CR18","doi-asserted-by":"crossref","unstructured":"Pitsikalis, M., Artikis, A., Dreo, R., Ray, C., Camossi, E., Jousselme, A.: Composite event recognition for maritime monitoring. In: DEBS, pp. 163\u2013174. ACM (2019)","DOI":"10.1145\/3328905.3329762"},{"key":"43_CR19","doi-asserted-by":"publisher","unstructured":"Ray, C., Dr\u00e9o, R., Camossi, E., Jousselme, A.L.: Heterogeneous integrated dataset for maritime intelligence, surveillance, and reconnaissance (2018). https:\/\/doi.org\/10.5281\/zenodo.1167595","DOI":"10.5281\/zenodo.1167595"},{"key":"43_CR20","unstructured":"Rosenberg, A., Hirschberg, J.: V-measure: a conditional entropy-based external cluster evaluation measure. In: EMNLP-CoNLL, pp. 410\u2013420. ACL (2007)"},{"key":"43_CR21","doi-asserted-by":"crossref","unstructured":"Shahir, A.Y., Charalampous, T., Tayebi, M.A., Gl\u00e4sser, U., Wehn, H.: Triptracker: unsupervised learning of fishing vessel routine activity patterns. In: IEEE BigData, pp. 1928\u20131939. IEEE (2021)","DOI":"10.1109\/BigData52589.2021.9671492"},{"key":"43_CR22","doi-asserted-by":"crossref","unstructured":"Vlachos, M., Vagena, Z., Yu, P.S., Athitsos, V.: Rotation invariant indexing of shapes and line drawings. In: CIKM, pp. 131\u2013138. ACM (2005)","DOI":"10.1145\/1099554.1099580"},{"key":"43_CR23","doi-asserted-by":"crossref","unstructured":"Wang, S., Bao, Z., Culpepper, J.S., Cong, G.: A survey on trajectory data management, analytics, and learning. ACM Comput. Surv. 54(2), 39:1\u201339:36 (2022)","DOI":"10.1145\/3440207"},{"key":"43_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2024.103426","volume":"183","author":"Y Yang","year":"2024","unstructured":"Yang, Y., Liu, Y., Li, G., Zhang, Z., Liu, Y.: Harnessing the power of machine learning for ais data-driven maritime research: a comprehensive review. Transp. Res. Part E Logist. Transp. Rev. 183, 103426 (2024)","journal-title":"Transp. Res. Part E Logist. Transp. Rev."}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-19105-2_43","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T22:18:30Z","timestamp":1778365110000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-19105-2_43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032191045","9783032191052"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-19105-2_43","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 May 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecmlpkdd.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}