{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T06:11:57Z","timestamp":1767852717701,"version":"3.49.0"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100010989","name":"University Alliance Ruhr","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010989","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,18]]},"DOI":"10.1109\/ijcnn54540.2023.10191405","type":"proceedings-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T17:30:03Z","timestamp":1690997403000},"page":"1-8","source":"Crossref","is-referenced-by-count":9,"title":["Evaluating and Comparing Heterogeneous Ensemble Methods for Unsupervised Anomaly Detection"],"prefix":"10.1109","author":[{"given":"Simon","family":"Kl\u00fcttermann","sequence":"first","affiliation":[{"name":"TU Dortmund University,Chair of Data Science and Data Engineering,Dortmund,Germany"}]},{"given":"Emmanuel","family":"M\u00fcller","sequence":"additional","affiliation":[{"name":"TU Dortmund University,Chair of Data Science and Data Engineering,Dortmund,Germany"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974973.11"},{"key":"ref35","author":"kl\u00fcttermann","year":"2023","journal-title":"yano"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/2481244.2481252"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1126\/science.1136800"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.12.042"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.143.1.7063747"},{"key":"ref14","author":"b\u00f6ing","year":"0","journal-title":"Post-robustifying deep anomaly detection ensembles by model selection"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1080\/15376494.2019.1609630"},{"key":"ref31","author":"odegua","year":"2019","journal-title":"An empirical study of ensemble techniques (bagging boosting and stacking)"},{"key":"ref30","article-title":"A linear method for deviation detection in large databases","author":"arning","year":"1996","journal-title":"Knowledge Discovery and data mining"},{"key":"ref11","article-title":"A study on anomaly detection ensembles","volume":"21","author":"chiang","year":"2016","journal-title":"Journal of Applied Logic"},{"key":"ref33","author":"sandim","year":"2017","journal-title":"Using stacked generalization for anomaly detection"},{"key":"ref10","article-title":"Adbench: Anomaly detection benchmark","author":"han","year":"2022","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972825.90"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116429"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.11.026"},{"key":"ref17","author":"gu","year":"2019","journal-title":"Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2021.3052449"},{"key":"ref19","article-title":"Deep one-class classification","author":"ruff","year":"2018","journal-title":"Proceedings of the 35th International Conference on Machine Learning"},{"key":"ref18","first-page":"93","volume":"29","author":"breunig","year":"2000","journal-title":"LOF Identifying Density-based Local Outliers"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01307-2_86"},{"key":"ref23","author":"shyu","year":"2003","journal-title":"A Novel Anomaly Detection Scheme Based on Principal Component Classifier"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(03)00003-5"},{"key":"ref25","author":"goldstein","year":"2012","journal-title":"Histogram-based outlier score (hbos) A fast unsupervised anomaly detection algorithm"},{"key":"ref20","first-page":"318","article-title":"Learning internal representations by error propagation","volume":"1","author":"rumelhart","year":"1986","journal-title":"Parallel Distributed Processing Explorations in the Microstructure of Cognition"},{"key":"ref22","volume":"12","author":"kingma","year":"2014","journal-title":"Auto-encoding variational bayes"},{"key":"ref21","article-title":"Support vector method for novelty detection","volume":"12","author":"sch\u00f6lkopf","year":"1999","journal-title":"Advances in neural information processing systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-47887-6_53"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-015-5521-0"},{"key":"ref29","author":"li","year":"2022","journal-title":"Ecod Unsupervised outlier detection using empirical cumulative distribution functions"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401946"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1111\/coin.12156"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00135"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/978-3-319-59050-9_12","article-title":"Unsupervised anomaly detection with generative adversarial networks to guide marker discovery","author":"schlegl","year":"2017","journal-title":"Information Processing in Medical Imaging"},{"key":"ref3","first-page":"149","article-title":"Healthcare and anomaly detection: Using machine learning to predict anomalies in heart rate data","volume":"36","author":"\u0161abi?","year":"2020","journal-title":"AI andSOCIETY"},{"key":"ref6","first-page":"413","author":"liu","year":"2009","journal-title":"Isolation forest"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177728190"}],"event":{"name":"2023 International Joint Conference on Neural Networks (IJCNN)","location":"Gold Coast, Australia","start":{"date-parts":[[2023,6,18]]},"end":{"date-parts":[[2023,6,23]]}},"container-title":["2023 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10190990\/10190992\/10191405.pdf?arnumber=10191405","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T17:45:40Z","timestamp":1692639940000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10191405\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,18]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/ijcnn54540.2023.10191405","relation":{},"subject":[],"published":{"date-parts":[[2023,6,18]]}}}