{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T13:17:47Z","timestamp":1768483067884,"version":"3.49.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T00:00:00Z","timestamp":1546473600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Ulster University VCRS Award"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2020,1]]},"DOI":"10.1007\/s10462-018-9671-x","type":"journal-article","created":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T10:08:51Z","timestamp":1546510131000},"page":"625-652","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Detecting anomalies in sequential data augmented with new features"],"prefix":"10.1007","volume":"53","author":[{"given":"Xiangzeng","family":"Kong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0979-4084","authenticated-orcid":false,"given":"Yaxin","family":"Bi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David H.","family":"Glass","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,3]]},"reference":[{"issue":"2015","key":"9671_CR1","doi-asserted-by":"publisher","first-page":"938","DOI":"10.1016\/j.eswa.2014.08.026","volume":"42","author":"I Aydin","year":"2015","unstructured":"Aydin I, Karakose M, Akin E (2015) Anomaly detection using a modified kernel-based tracking in the pantograph-catenary system. Expert Syst Appl 42(2015):938\u2013948","journal-title":"Expert Syst Appl"},{"issue":"5","key":"9671_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1147\/JRD.2011.2163280","volume":"55","author":"MS Beigi","year":"2011","unstructured":"Beigi MS, Chang SF, Ebadollahi S, Verma DC (2011) Anomaly detection in information streams without prior domain knowledge. IBM J Res Dev 55(5):1\u201311","journal-title":"IBM J Res Dev"},{"key":"9671_CR3","doi-asserted-by":"crossref","unstructured":"Breunig MM, Kriegel H-P, Ng RN, Sander J (2000) LOF: identifying density-based local outliers. In: Proceeding SIGMOD\u201900 proceedings of the 2000 ACM SIGMOD international conference on management of data, vol 29(2). ACM, New York, pp 93\u2013104","DOI":"10.1145\/342009.335388"},{"key":"9671_CR4","unstructured":"Chandola V, Boriah S, Kumar V (2008a) Understanding categorical similarity measures for outlier detection. Technical report 08-008, University of Minnesota, pp 1\u201345"},{"key":"9671_CR5","doi-asserted-by":"crossref","unstructured":"Chandola V, Mithal V, Kumar V (2008b) A comparative evaluation of anomaly detection techniques for sequence data. In: ICDM, pp 743\u2013748","DOI":"10.1109\/ICDM.2008.151"},{"issue":"3","key":"9671_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1541880.1541882","volume":"41","author":"V Chandola","year":"2009","unstructured":"Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: a survey. ACM Comput Surv 41(3):1\u201358","journal-title":"ACM Comput Surv"},{"issue":"9","key":"9671_CR8","doi-asserted-by":"publisher","first-page":"2250","DOI":"10.1109\/TKDE.2013.184","volume":"26","author":"M Gupta","year":"2014","unstructured":"Gupta M, Gao J, Aggarwal CC, Han J (2014) Outlier detection for temporal data: a survey. IEEE Trans Knowl Data Eng 26(9):2250\u20132267","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"9671_CR9","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1111\/j.2517-6161.1994.tb01988.x","volume":"56","author":"AS Hadi","year":"1994","unstructured":"Hadi AS (1994) A modification of a method for the detection of outliers in multivariate samples. J R Stat Soc B 56(2):393\u2013396","journal-title":"J R Stat Soc B"},{"issue":"2","key":"9671_CR10","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1023\/B:AIRE.0000045502.10941.a9","volume":"22","author":"VJ Hodge","year":"2004","unstructured":"Hodge VJ, Austin J (2004) A survey of outlier detection methodologies. Artif Intell Rev 22(2):85\u2013126","journal-title":"Artif Intell Rev"},{"key":"9671_CR11","unstructured":"Huang H (2013) Rank based anomaly detection algorithms. Dissertations, Electrical Engineering and Computer Science, pp 1\u2013182"},{"issue":"9","key":"9671_CR12","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.1109\/TIM.2016.2570398","volume":"65","author":"XH Jin","year":"2016","unstructured":"Jin XH, Sun Y, Que ZJ, Wang Y, Chow WS (2016) Anomaly detection and fault prognosis for bearings. IEEE Trans Instrum Meas 65(9):2046\u20132054","journal-title":"IEEE Trans Instrum Meas"},{"key":"9671_CR13","doi-asserted-by":"crossref","unstructured":"Keogh E, Chakrabarti K, Pazzani M, Mehrotra S (2001) Dimensionality reduction for fast similarity search in large time series databases. In: Proceedings of the ACM SIGMOD international conference on management of data, pp 151\u2013162","DOI":"10.1145\/376284.375680"},{"key":"9671_CR14","first-page":"206","volume-title":"Towards parameter-free data mining","author":"E Keogh","year":"2004","unstructured":"Keogh E, Lonardi S, Ratanamahatana CA (2004) Towards parameter-free data mining. KDD, Seattle, Washington, DC, pp 206\u2013215"},{"key":"9671_CR15","doi-asserted-by":"crossref","unstructured":"Keogh E, Lin J, Fu A (2005) Hot sax: efficiently finding the most unusual time series subsequence. In: ICDM, pp 226\u2013233","DOI":"10.1109\/ICDM.2005.79"},{"issue":"1","key":"9671_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-006-0034-6","volume":"11","author":"Eamonn Keogh","year":"2006","unstructured":"Keogh E, Lin J, Lee SH, Herle HV (2006) Finding the most unusual time series subsequence: algorithms and applications. Knowl Inf Syst 11(1):1\u201327. http:\/\/www.cs.ucr.edu\/~eamonn\/","journal-title":"Knowledge and Information Systems"},{"issue":"3","key":"9671_CR17","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/PL00011669","volume":"3","author":"E Keogh","year":"2008","unstructured":"Keogh E, Chakrabarti K, Pazzani MJ, Mehrotra S (2008) Dimensionality reduction for fast similarity search in large time series databases. Knowl Inf Syst 3(3):263\u2013268","journal-title":"Knowl Inf Syst"},{"key":"9671_CR18","doi-asserted-by":"crossref","unstructured":"Kou Y, Lu CT, Chen D (2006) Spatial weighted outlier detection. In: Proceedings of the SIAM conference on data mining, pp 614\u2013617","DOI":"10.1137\/1.9781611972764.71"},{"key":"9671_CR19","doi-asserted-by":"crossref","unstructured":"Lin J, Keogh E, Lonardi S, Chiu B (2003) A symbolic representation of time series, with implications for streaming algorithms. In: Proceedings of the 8th ACM SIGMOD workshop on research issues in data mining and knowledge discovery, pp 2\u201311","DOI":"10.1145\/882082.882086"},{"key":"9671_CR20","doi-asserted-by":"crossref","unstructured":"Palpanas T, Vlachos M, Keogh E, Gunopulos D, Truppel W (2004) Online amnesic approximation of streaming time series. In: ICDE, Boston, March 2004","DOI":"10.1109\/ICDE.2004.1320009"},{"key":"9671_CR21","doi-asserted-by":"crossref","unstructured":"Park S, Kim SW, Cho JS, Padmanabhan S (2001a) Prefix-querying: an approach for effective subsequence matching under time warping in sequence databases. In: Proceedings of the 10th international conference on information and knowledge management, pp 255\u2013262","DOI":"10.1145\/502585.502629"},{"key":"9671_CR22","doi-asserted-by":"crossref","unstructured":"Park S, Kim SW, Chu WW (2001b) Segment-based approach for subsequence searches in sequence databases. In: Proceedings of the 16th ACM symposium on applied computing, pp 248\u2013252","DOI":"10.1145\/372202.372334"},{"key":"9671_CR23","unstructured":"Peng CS, Wang H, Zhang SR, Parker DS (2000) Landmarks: a new model for similarity-based pattern querying in time series databases. In: Proceedings of the 16th international conference on data engineering, pp 33\u201342"},{"issue":"1","key":"9671_CR24","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1142\/S0219467802000482","volume":"2","author":"KB Pratt","year":"2002","unstructured":"Pratt KB, Fink E (2002) Search for patterns in compressed time series. Int J Image Graph\u00a02(1):89\u2013106","journal-title":"Int J Image Graph"},{"key":"9671_CR25","doi-asserted-by":"crossref","unstructured":"Ramaswamy S, Rastogi R, Kyuseok S (2000) Efficient algorithms for mining outliers from large data sets. In: Proceeding ACMSIGMOD international conference on management of data, pp 427\u2013438","DOI":"10.1145\/335191.335437"},{"key":"9671_CR26","unstructured":"Sun J, Qu H, Chakrabarti D, Faloutsos C (2005) Neighborhood formation and anomaly detection in bipartite graphs. In: Proceedings of the 5th IEEE international conference on data mining. IEEE Computer Society, pp 418\u2013425"},{"key":"9671_CR27","doi-asserted-by":"crossref","unstructured":"Tandon G, Chan P (2007) Weighting versus pruning in rule validation for detecting network and host anomalies. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 697\u2013706","DOI":"10.1145\/1281192.1281267"},{"issue":"4","key":"9671_CR29","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1142\/S0129065795000251","volume":"6","author":"AS Weigend","year":"1995","unstructured":"Weigend AS, Mangeas M, Srivastava AN (1995) Nonlinear gated experts for time-series: discovering regimes and avoiding overfitting. Int J Neural Syst 6(4):373\u2013399","journal-title":"Int J Neural Syst"},{"issue":"9","key":"9671_CR30","doi-asserted-by":"publisher","first-page":"2747","DOI":"10.12733\/jics20101797","volume":"10","author":"C Yan","year":"2013","unstructured":"Yan C, Fang J, Wu L, Ma S (2013) An approach of time series piecewise linear representation based on local maximum minimum and extremum. J Inf Comput Sci 10(9):2747\u20132756","journal-title":"J Inf Comput Sci"},{"key":"9671_CR31","doi-asserted-by":"crossref","unstructured":"Yankov D, Keogh E, Rebbapragada U (2007) Disk aware discord discovery: finding unusual time series in terabyte sized datasets. In: ICDM 2007","DOI":"10.1109\/ICDM.2007.61"},{"key":"9671_CR32","unstructured":"Zhang Y, Meratnia N, Havinga PJM (2008) Outlier detection techniques for wireless sensor networks: a survey. Technical Report, Centre Telemat. Inform. Technol. Univ. Twente, Enschede, TR-CTIT-08-59, pp 159\u2013170"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-018-9671-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10462-018-9671-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-018-9671-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,13]],"date-time":"2024-07-13T19:48:09Z","timestamp":1720900089000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10462-018-9671-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,3]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,1]]}},"alternative-id":["9671"],"URL":"https:\/\/doi.org\/10.1007\/s10462-018-9671-x","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,3]]},"assertion":[{"value":"3 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}