{"title":"Comparative Evaluation of Anomaly Detection Techniques for Sequence Data","authors":"V. Chandola, Varun Mithal, Vipin Kumar","doi":"10.1109/ICDM.2008.151","DOIUrl":null,"url":null,"abstract":"We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.","PeriodicalId":252958,"journal":{"name":"2008 Eighth IEEE International Conference on Data Mining","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"165","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Eighth IEEE International Conference on Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDM.2008.151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 165
Abstract
We present a comparative evaluation of a large number of anomaly detection techniques on a variety of publicly available as well as artificially generated data sets. Many of these are existing techniques while some are slight variants and/or adaptations of traditional anomaly detection techniques to sequence data.