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Detection and Implicit Classification of Outliers via Different Feature Sets in Polygonal Chains.

, , , and . BTW, volume P-265 of LNI, page 237-246. GI, (2017)

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Cluster-based stability evaluation in time series data sets., , and . Appl. Intell., 53 (13): 16606-16629 (July 2023)Loners Stand Out. Identification of Anomalous Subsequences Based on Group Performance., , and . ADMA, volume 12447 of Lecture Notes in Computer Science, page 360-369. Springer, (2020)Clustering of Time Series Regarding Their Over-Time Stability., , and . SSCI, page 1051-1058. IEEE, (2020)Behave or Be Detected! Identifying Outlier Sequences by Their Group Cohesion., , and . DaWaK, volume 12393 of Lecture Notes in Computer Science, page 333-347. Springer, (2020)Illuminating the Predictive Power of Gamification to Inspire Technology Users., , , and . MuC (Workshopband), Gesellschaft für Informatik e.V., (2023)Overcoming Inefficiency in Public Procurement: An OpenData Approach., , , and . GI-Jahrestagung, volume P-337 of LNI, page 1097-1102. Gesellschaft für Informatik, Bonn, (2023)Shape Based Outlier Detection in SLIC Superpixels., and . Grundlagen von Datenbanken, volume 1858 of CEUR Workshop Proceedings, page 60-65. CEUR-WS.org, (2017)Show Me Your Friends and I'll Tell You Who You Are. Finding Anomalous Time Series by Conspicuous Cluster Transitions., , , and . AusDM, volume 1127 of Communications in Computer and Information Science, page 91-103. Springer, (2019)Fuzzy Clustering Stability Evaluation of Time Series., , , and . IPMU (1), volume 1237 of Communications in Computer and Information Science, page 680-692. Springer, (2020)Pattern Discovery in Time Series.. University of Düsseldorf, Germany, (2021)