Tensor-based anomaly detection: An interdisciplinary survey

• Tipo: Artigo em Revista Científica Internacional
• Data: 2016

Autores

Fanaee T, H (Autor) Outra; João Gama (Autor) FEP

Revista

Título: Knowledge-Based Systems

Vol. 98

Páginas: 130-147

ISSN: 0950-7051

Editora: Elsevier

Indexação

ISI Web of Knowledge - 99 Citações

Scopus - 120 Citações

Outras Informações

ID Authenticus: P-00K-7MR

DOI: 10.1016/j.knosys.2016.01.027

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 18