Anomaly detection in spatiotemporal data via regularized non-negative tensor analysis

DOI10.1007/S10618-018-0560-3zbMath1416.62292OpenAlexW2794774115WikidataQ130019205 ScholiaQ130019205MaRDI QIDQ1741411

Zhuochen Jin, Chaoguang Lin, Shunan Guo, Qiuhan Zhu, Nan Cao, Yu-Ru Lin

Publication date: 3 May 2019

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: http://d-scholarship.pitt.edu/34720/1/Lin2018_Article_AnomalyDetectionInSpatiotempor.pdf

zbMATH Keywords

outlier detectiontensor analysisanomaly detectiontraffic analysisurban computing

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Applications of statistics to economics (62P20) Traffic problems in operations research (90B20)

Uses Software

• LOF

Cites Work

• Tensor Decompositions and Applications
• Higher rank support tensor machines for visual recognition
• Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework

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