{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T22:08:12Z","timestamp":1767650892118,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,12]]},"DOI":"10.1109\/bigdata.2016.7841051","type":"proceedings-article","created":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T16:46:59Z","timestamp":1486486019000},"page":"3798-3806","source":"Crossref","is-referenced-by-count":28,"title":["Vessel movement analysis and pattern discovery using density-based clustering approach"],"prefix":"10.1109","author":[{"given":"Wenjing","family":"Yan","sequence":"first","affiliation":[]},{"given":"Rong","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Allan N.","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Dazhi","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"year":"0","key":"ref10"},{"year":"0","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2007.10.008"},{"key":"ref13","first-page":"22:1","article-title":"A model for enriching trajectories with semantic geographical information","author":"alvares","year":"0"},{"key":"ref14","first-page":"863","article-title":"A clusteringbased approach for discovering interesting places in trajectories","author":"palma","year":"0"},{"key":"ref15","first-page":"114","article-title":"DB-SMoT: A Direction-Based Spatio-Temporal Clustering Method","author":"manso","year":"0"},{"article-title":"Data Mining: Concepts and Techniques","year":"2011","author":"han","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/e15062218"},{"article-title":"Traffic knowledge discovery from AIS data","year":"0","author":"pallotta","key":"ref18"},{"key":"ref19","first-page":"1152","article-title":"Data-driven Detection and Context-based Classification of Maritime Anomalies","author":"giuliana pallotta","year":"2015","journal-title":"14th International Conference on Information Fusion (FUSION)"},{"year":"0","key":"ref4"},{"key":"ref3","article-title":"Efficient AIS Data Processing for Environmentally Safe Shipping","volume":"63","author":"vodas","year":"2013","journal-title":"SPOUDAI-Journal of Economics and Business"},{"key":"ref6","first-page":"1","article-title":"Statistical analysis of motion patterns in AIS Data: Anomaly detection and motion prediction","author":"ristic","year":"2008","journal-title":"2008 11th International Conference on Information Fusion FUSION"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2014.6946815"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1049\/cp.2012.0414"},{"key":"ref7","first-page":"756","article-title":"anomaly detection in sea traffic - a comparison of the gaussian mixture model and the kernel density estimator","author":"laxhammar","year":"2009","journal-title":"2009 12th International Conference on Information Fusion fusion"},{"year":"0","key":"ref2"},{"year":"0","key":"ref1","article-title":"International Convention for the Safety of Life at Sea (SOLAS)"},{"key":"ref9","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","author":"ester","year":"1996","journal-title":"Proceedings of the International Conference on Knowledge Discovery and Data Mining"},{"key":"ref20","first-page":"1","article-title":"Automatic generation of geographical networks for maritime traffic surveillance","author":"arguedas","year":"2014","journal-title":"Information Fusion (FUSION)"},{"article-title":"Spatio-temporal Route Mining and Visualization for Busy Waterways","year":"0","author":"wen","key":"ref22"},{"article-title":"Abnormal Vessel Behavior Detection in Port Areas Based on Dynamic Bayesian Networks","year":"0","author":"castaldo","key":"ref21"}],"event":{"name":"2016 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2016,12,5]]},"location":"Washington DC,USA","end":{"date-parts":[[2016,12,8]]}},"container-title":["2016 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7818133\/7840573\/07841051.pdf?arnumber=7841051","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,12,13]],"date-time":"2017-12-13T15:38:46Z","timestamp":1513179526000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7841051\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2016.7841051","relation":{},"subject":[],"published":{"date-parts":[[2016,12]]}}}