Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5381
Title: Tensor-based anomaly detection: An interdisciplinary survey
Authors: Hadi Fanaee Tork
João Gama
Issue Date: 2016
Abstract: Traditional spectral-based methods such as PCA are popular for anomaly detection in a variety of problems and domains. However, if data includes tensor (multiway) structure (e.g. space-time-measurements), some meaningful anomalies may remain invisible with these methods. Although tensor-based anomaly detection (TAD) has been applied within a variety of disciplines over the last twenty years, it is not yet recognized as a formal category in anomaly detection. This survey aims to highlight the potential of tensor-based techniques as a novel approach for detection and identification of abnormalities and failures. We survey the interdisciplinary works in which TAD is reported and characterize the learning strategies, methods and applications; extract the important open issues in TAD and provide the corresponding existing solutions according to the state-of-the-art.
URI: http://repositorio.inesctec.pt/handle/123456789/5381
http://dx.doi.org/10.1016/j.knosys.2016.01.027
metadata.dc.type: article
Publication
Appears in Collections:LIAAD - Articles in International Journals

Files in This Item:
File Description SizeFormat 
P-00K-7MR.pdf1.07 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.