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 …
Trajectory data mining: an overview
Y Zheng - ACM Transactions on Intelligent Systems and …, 2015 - dl.acm.org
The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …
Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting
Traffic forecasting is a challenging problem due to the complexity of jointly modeling spatio‐
temporal dependencies at different scales. Recently, several hybrid deep learning models …
temporal dependencies at different scales. Recently, several hybrid deep learning models …
Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Spatiotemporal forecasting has various applications in neuroscience, climate and
transportation domain. Traffic forecasting is one canonical example of such learning task …
transportation domain. Traffic forecasting is one canonical example of such learning task …
Spatial-temporal transformer networks for traffic flow forecasting
Traffic forecasting has emerged as a core component of intelligent transportation systems.
However, timely accurate traffic forecasting, especially long-term forecasting, still remains an …
However, timely accurate traffic forecasting, especially long-term forecasting, still remains an …
Deep learning: A generic approach for extreme condition traffic forecasting
Traffic forecasting is a vital part of intelligent transportation systems. It becomes particularly
challenging due to short-term (eg, accidents, constructions) and long-term (eg, peak-hour …
challenging due to short-term (eg, accidents, constructions) and long-term (eg, peak-hour …
Urban computing: concepts, methodologies, and applications
Urbanization's rapid progress has modernized many people's lives but also engendered big
issues, such as traffic congestion, energy consumption, and pollution. Urban computing …
issues, such as traffic congestion, energy consumption, and pollution. Urban computing …
Methodologies for cross-domain data fusion: An overview
Y Zheng - IEEE transactions on big data, 2015 - ieeexplore.ieee.org
Traditional data mining usually deals with data from a single domain. In the big data era, we
face a diversity of datasets from different sources in different domains. These datasets …
face a diversity of datasets from different sources in different domains. These datasets …
Discovering regions of different functions in a city using human mobility and POIs
The development of a city gradually fosters different functional regions, such as educational
areas and business districts. In this paper, we propose a framework (titled DRoF) that …
areas and business districts. In this paper, we propose a framework (titled DRoF) that …
Discovering urban functional zones using latent activity trajectories
The step of urbanization and modern civilization fosters different functional zones in a city,
such as residential areas, business districts, and educational areas. In a metropolis, people …
such as residential areas, business districts, and educational areas. In a metropolis, people …