dc.contributor.author | Γαβαλάς, Νικόλαος![]() |
el |
dc.contributor.author | Gavalas, Nikolaos![]() |
en |
dc.date.accessioned | 2019-07-12T11:05:57Z | |
dc.date.available | 2019-07-12T11:05:57Z | |
dc.date.issued | 2019-07-12 | |
dc.identifier.uri | https://dspace.lib.ntua.gr/xmlui/handle/123456789/49060 | |
dc.identifier.uri | http://dx.doi.org/10.26240/heal.ntua.16500 | |
dc.rights | Αναφορά Δημιουργού 3.0 Ελλάδα | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/gr/ | * |
dc.subject | Machine learning | en |
dc.subject | Big data | en |
dc.subject | Anomaly detection | en |
dc.subject | Distributed stream processing | en |
dc.subject | Real-time systems | en |
dc.subject | Συστήματα πραγματικού χρόνου | el |
dc.subject | Μηχανική μάθηση | el |
dc.subject | Ανίχνευση ανωμαλιών | el |
dc.subject | Κατανεμημένη επεργασία ροής | el |
dc.title | Real-time anomaly detection at scale | en |
heal.type | bachelorThesis | |
heal.classification | Computer engineering | en |
heal.language | en | |
heal.access | free | |
heal.recordProvider | ntua | el |
heal.publicationDate | 2019-03-13 | |
heal.abstract | Anomaly Detection is a field of Machine Learning used by systems to identify observations that differ from the majority of data and are often linked directly to unexpected behaviour, errors, and other forms of novelties.Common applications of Anomaly Detection include but are not limited to credit card fraud detection, machinery or computer behaviour monitoring, network intrusion detection, real-time analytics, etc. In this thesis we study algorithms and methods for Anomaly Detection that enable identification of outliers both in real-time, in order to prevent unwanted events as soon as possible, and at a big scale, since the volume of data in our era is growing exponentially. | en |
heal.advisorName | Κοζύρης, Νεκτάριος | el |
heal.committeeMemberName | Κοζύρης, Νεκτάριος | el |
heal.committeeMemberName | Γκούμας, Γεώργιος | el |
heal.committeeMemberName | Τσουμάκος, Δημήτριος | el |
heal.academicPublisher | Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Τεχνολογίας Πληροφορικής και Υπολογιστών. Εργαστήριο Υπολογιστικών Συστημάτων | el |
heal.academicPublisherID | ntua | |
heal.numberOfPages | 71 σ. | el |
heal.fullTextAvailability | true |
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