Deep learning for spatio-temporal data mining: A survey
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
An overview of microblog user geolocation methods
X Luo, Y Qiao, C Li, J Ma, Y Liu - Information processing & management, 2020 - Elsevier
Geographical locations of microblog users are essential for user profiling, event localization
and target advertising, to name a few. Automatic identification of user locations from the …
and target advertising, to name a few. Automatic identification of user locations from the …
Modeling extreme events in time series prediction
Time series prediction is an intensively studied topic in data mining. In spite of the
considerable improvements, recent deep learning-based methods overlook the existence of …
considerable improvements, recent deep learning-based methods overlook the existence of …
Fido: Ubiquitous fine-grained wifi-based localization for unlabelled users via domain adaptation
To fully support the emerging location-aware applications, location information with meter-
level resolution (or even higher) is required anytime and anywhere. Unfortunately, most of …
level resolution (or even higher) is required anytime and anywhere. Unfortunately, most of …
[HTML][HTML] Assessing the influence of point-of-interest features on the classification of place categories
V Milias, A Psyllidis - Computers, Environment and Urban Systems, 2021 - Elsevier
Points of interest (POIs) digitally represent real-world amenities as point locations. POI
categories (eg restaurant, hotel, museum etc.) play a prominent role in several location …
categories (eg restaurant, hotel, museum etc.) play a prominent role in several location …
Semantic-aware privacy-preserving online location trajectory data sharing
Although users can obtain various services by sharing their location information online with
location-based service providers, it reveals sensitive information about users. However …
location-based service providers, it reveals sensitive information about users. However …
深度学习在时空序列预测中的应用综述.
刘博， 王明烁， 李永， 陈洪丽… - Journal of Beijing …, 2021 - search.ebscohost.com
摘摇要: 对深度学习模型应用于时空序列预测的最新进展进行总结. 首先介绍时空序列数据的
属性及类型, 并进行相应的实例化与表示. 接着针对时空序列数据存在的3 …
属性及类型, 并进行相应的实例化与表示. 接着针对时空序列数据存在的3 …
Dual subgraph-based graph neural network for friendship prediction in location-based social networks
With the wide use of Location-Based Social Networks (LBSNs), predicting user friendship
from online social relations and offline trajectory data is of great value to improve the …
from online social relations and offline trajectory data is of great value to improve the …
Transfer urban human mobility via poi embedding over multiple cities
Rapidly developing location acquisition technologies provide a powerful tool for
understanding and predicting human mobility in cities, which is very significant for urban …
understanding and predicting human mobility in cities, which is very significant for urban …
[HTML][HTML] Neural networks for intelligent multilevel control of artificial and natural objects based on data fusion: A survey
T Man, VY Osipov, N Zhukova, A Subbotin, DI Ignatov - Information Fusion, 2024 - Elsevier
Today the tasks of complex artificial and natural objects control have come to the fore in the
majority of subject domains. The efficiency and effectiveness of solving these tasks directly …
majority of subject domains. The efficiency and effectiveness of solving these tasks directly …