Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/83028
Author(s): T, HF
João Gama
Title: An eigenvector-based hotspot detection
Issue Date: 2014
Abstract: Space and time are two critical components of many real world systems. For thisreason, analysis of anomalies in spatiotemporal data has been a great of interest.In this work, application of tensor decomposition and eigenspace techniques on spa-tiotemporal hotspot detection is investigated. An algorithm called SST-Hotspot isproposed which accounts for spatiotemporal variations in data and detect hotspotsusing matching of eigenvector elements of two cases and population tensors. Theexperimental results reveal the interesting application of tensor decomposition andeigenvector-based techniques in hotspot analysis.
URI: https://repositorio-aberto.up.pt/handle/10216/83028
Document Type: Artigo em Revista Científica Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEP - Artigo em Revista Científica Internacional

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