Urban big data fusion based on deep learning: An overview
Urban big data fusion creates huge values for urban computing in solving urban problems.
In recent years, various models and algorithms based on deep learning have been …
In recent years, various models and algorithms based on deep learning have been …
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 …
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 …
A federated learning approach to anomaly detection in smart buildings
Internet of Things (IoT) sensors in smart buildings are becoming increasingly ubiquitous,
making buildings more livable, energy efficient, and sustainable. These devices sense the …
making buildings more livable, energy efficient, and sustainable. These devices sense the …
RiskOracle: A minute-level citywide traffic accident forecasting framework
Real-time traffic accident forecasting is increasingly important for public safety and urban
management (eg, real-time safe route planning and emergency response deployment) …
management (eg, real-time safe route planning and emergency response deployment) …
Spatio-temporal analysis of passenger travel patterns in massive smart card data
Metro systems have become one of the most important public transit services in cities. It is
important to understand individual metro passengers' spatio-temporal travel patterns. More …
important to understand individual metro passengers' spatio-temporal travel patterns. More …
Urban water quality prediction based on multi-task multi-view learning
Urban water quality is of great importance to our daily lives. Prediction of urban water quality
help control water pollution and protect human health. In this work, we forecast the water …
help control water pollution and protect human health. In this work, we forecast the water …
Data fusion in cyber-physical-social systems: State-of-the-art and perspectives
Abstract Cyber-Physical-Social systems (CPSSs) are the extension of Cyber-Physical
systems (CPS), which seamlessly integrate cyber space, physical space and social space …
systems (CPS), which seamlessly integrate cyber space, physical space and social space …
Foresee urban sparse traffic accidents: A spatiotemporal multi-granularity perspective
Traffic accident has become a significant health and development threat with rapid
urbanizations. An accurate urban accident forecasting enables higher-quality police force …
urbanizations. An accurate urban accident forecasting enables higher-quality police force …
Mist: A multiview and multimodal spatial-temporal learning framework for citywide abnormal event forecasting
Citywide abnormal events, such as crimes and accidents, may result in loss of lives or
properties if not handled efficiently. It is important for a wide spectrum of applications …
properties if not handled efficiently. It is important for a wide spectrum of applications …