A review on outlier/anomaly detection in time series data
Recent advances in technology have brought major breakthroughs in data collection,
enabling a large amount of data to be gathered over time and thus generating time series …
enabling a large amount of data to be gathered over time and thus generating time series …
[BOOK][B] An introduction to outlier analysis
CC Aggarwal, CC Aggarwal - 2017 - Springer
Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …
mining and statistics literature. In most applications, the data is created by one or more …
Outlier detection for temporal data: A survey
In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …
decades. Recently, with advances in hardware and software technology, there has been a …
Spatio-temporal data mining: A survey of problems and methods
Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …
domains, including climate science, social sciences, neuroscience, epidemiology …
Graph convolutional adversarial networks for spatiotemporal anomaly detection
Traffic anomalies, such as traffic accidents and unexpected crowd gathering, may endanger
public safety if not handled timely. Detecting traffic anomalies in their early stage can benefit …
public safety if not handled timely. Detecting traffic anomalies in their early stage can benefit …
Anomaly detection of time series with smoothness-inducing sequential variational auto-encoder
Deep generative models have demonstrated their effectiveness in learning latent
representation and modeling complex dependencies of time series. In this article, we …
representation and modeling complex dependencies of time series. In this article, we …
Anomaly detection in dynamic networks: a survey
Anomaly detection is an important problem with multiple applications, and thus has been
studied for decades in various research domains. In the past decade there has been a …
studied for decades in various research domains. In the past decade there has been a …
From taxi GPS traces to social and community dynamics: A survey
Vehicles equipped with GPS localizers are an important sensory device for examining
people's movements and activities. Taxis equipped with GPS localizers serve the …
people's movements and activities. Taxis equipped with GPS localizers serve the …
iBAT: detecting anomalous taxi trajectories from GPS traces
GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces
produced allow us to reveal many hidden" facts" about the city dynamics and human …
produced allow us to reveal many hidden" facts" about the city dynamics and human …
Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework
Vehicle detection in traffic surveillance images is an important approach to obtain vehicle
data and rich traffic flow parameters. Recently, deep learning based methods have been …
data and rich traffic flow parameters. Recently, deep learning based methods have been …