{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:34:00Z","timestamp":1771702440198,"version":"3.50.1"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319244884","type":"print"},{"value":"9783319244891","type":"electronic"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-24489-1_24","type":"book-chapter","created":{"date-parts":[[2015,9,29]],"date-time":"2015-09-29T07:00:40Z","timestamp":1443510040000},"page":"279-286","source":"Crossref","is-referenced-by-count":18,"title":["Event Detection in Marine Time Series Data"],"prefix":"10.1007","author":[{"given":"Stefan","family":"Oehmcke","sequence":"first","affiliation":[]},{"given":"Oliver","family":"Zielinski","sequence":"additional","affiliation":[]},{"given":"Oliver","family":"Kramer","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,11,3]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Auslander, B., Gupta, K.M., Aha, D.W.: A comparative evaluation of anomaly detection algorithms for maritime video surveillance. In: SPIE Defense, Security, and Sensing, pp. 801907\u2013801907. International Society for Optics and Photonics (2011)","DOI":"10.1117\/12.883535"},{"issue":"2","key":"24_CR2","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s10236-009-0183-8","volume":"59","author":"TH Badewien","year":"2009","unstructured":"Badewien, T.H., Zimmer, E., Bartholom\u00e4, A., Reuter, R.: Towards continuous long-term measurements of suspended particulate matter (SPM) in turbid coastal waters. Ocean Dynamics 59(2), 227\u2013238 (2009)","journal-title":"Ocean Dynamics"},{"issue":"2","key":"24_CR3","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s10115-006-0026-6","volume":"11","author":"S Basu","year":"2007","unstructured":"Basu, S., Meckesheimer, M.: Automatic outlier detection for time series: an application to sensor data. Knowledge and Information Systems 11(2), 137\u2013154 (2007)","journal-title":"Knowledge and Information Systems"},{"key":"24_CR4","doi-asserted-by":"crossref","unstructured":"Breunig, M.M., Kriegel, H.P., Ng, R.T., Sander, J.: Lof: identifying density-based local outliers. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, SIGMOD 2000, pp. 93\u2013104. ACM (2000)","DOI":"10.1145\/335191.335388"},{"issue":"3","key":"24_CR5","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 Computing Surveys (CSUR) 41(3), 15 (2009)","journal-title":"ACM Computing Surveys (CSUR)"},{"issue":"2","key":"24_CR6","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1137\/0717021","volume":"17","author":"FN Fritsch","year":"1980","unstructured":"Fritsch, F.N., Carlson, R.E.: Monotone piecewise cubic interpolation. SIAM Journal on Numerical Analysis 17(2), 238\u2013246 (1980)","journal-title":"SIAM Journal on Numerical Analysis"},{"issue":"1","key":"24_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00573ED1V01Y201403DMK008","volume":"5","author":"M Gupta","year":"2014","unstructured":"Gupta, M., Gao, J., Aggarwal, C., Han, J.: Outlier detection for temporal data. Synthesis Lectures on Data Mining and Knowledge Discovery 5(1), 1\u2013129 (2014)","journal-title":"Synthesis Lectures on Data Mining and Knowledge Discovery"},{"key":"24_CR8","doi-asserted-by":"crossref","unstructured":"Jin, W., Tung, A.K., Han, J.: Mining top-n local outliers in large databases. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 293\u2013298. ACM (2001)","DOI":"10.1145\/502512.502554"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Kriegel, H.P., Kr\u00f6ger, P., Schubert, E., Zimek, A.: Interpreting and unifying outlier scores. In: SDM, pp. 13\u201324. SIAM (2011)","DOI":"10.1137\/1.9781611972818.2"},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Li, X., Han, J., Kim, S., Gonzalez, H.: Roam: rule-and motif-based anomaly detection in massive moving object data sets. In: SDM, vol. 7, pp. 273\u2013284. SIAM (2007)","DOI":"10.1137\/1.9781611972771.25"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Liu, F.T., Ting, K.M., Zhou, Z.H.: Isolation forest. In: Eighth IEEE International Conference on Data Mining, ICDM 2008, pp. 413\u2013422. IEEE (2008)","DOI":"10.1109\/ICDM.2008.17"},{"issue":"1","key":"24_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11063-009-9106-4","volume":"30","author":"AP Modenesi","year":"2009","unstructured":"Modenesi, A.P., Braga, A.P.: Analysis of time series novelty detection strategies for synthetic and real data. Neural Processing Letters 30(1), 1\u201317 (2009)","journal-title":"Neural Processing Letters"},{"issue":"2","key":"24_CR13","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s10236-009-0196-3","volume":"59","author":"R Reuter","year":"2009","unstructured":"Reuter, R., Badewien, T.H., Bartholom\u00e4, A., Braun, A., L\u00fcbben, A., Rullk\u00f6tter, J.: A hydrographic time series station in the wadden sea (southern north sea). Ocean Dynamics 59(2), 195\u2013211 (2009)","journal-title":"Ocean Dynamics"},{"key":"24_CR14","unstructured":"Riveiro, M., Falkman, G., Ziemke, T.: Improving maritime anomaly detection and situation awareness through interactive visualization. In: 2008 11th International Conference on Information Fusion, pp. 1\u20138. IEEE (2008)"},{"issue":"5500","key":"24_CR15","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","volume":"290","author":"JB Tenenbaum","year":"2000","unstructured":"Tenenbaum, J.B., De Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319\u20132323 (2000)","journal-title":"Science"},{"issue":"3","key":"24_CR16","doi-asserted-by":"publisher","first-page":"329","DOI":"10.5194\/os-5-329-2009","volume":"5","author":"O Zielinski","year":"2009","unstructured":"Zielinski, O., Busch, J.A., Cembella, A.D., Daly, K.L., Engelbrektsson, J., Hannides, A.K., Schmidt, H.: Detecting marine hazardous substances and organisms: sensors for pollutants, toxins, and pathogens. Ocean Science 5(3), 329\u2013349 (2009)","journal-title":"Ocean Science"}],"container-title":["Lecture Notes in Computer Science","KI 2015: Advances in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-24489-1_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T02:35:26Z","timestamp":1559270126000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-24489-1_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319244884","9783319244891"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-24489-1_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]}}}