Intelligent electric vehicle charging recommendation based on multi-agent reinforcement learning
Electric Vehicle (EV) has become a preferable choice in the modern transportation system
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
Contrastive graph learning long and short-term interests for POI recommendation
Modeling users' short-term dynamic and long-term static interests to enhance Point-of-
Interests (POI) recommendation performance has shown lots of advantages. Since users' …
Interests (POI) recommendation performance has shown lots of advantages. Since users' …
Graph neural pre-training for recommendation with side information
Leveraging the side information associated with entities (ie, users and items) to enhance
recommendation systems has been widely recognized as an essential modeling dimension …
recommendation systems has been widely recognized as an essential modeling dimension …
GNN at the edge: Cost-efficient graph neural network processing over distributed edge servers
Edge intelligence has arisen as a promising computing paradigm for supporting
miscellaneous smart applications that rely on machine learning techniques. While the …
miscellaneous smart applications that rely on machine learning techniques. While the …
Hgamn: Heterogeneous graph attention matching network for multilingual poi retrieval at baidu maps
The increasing interest in international travel has raised the demand of retrieving point of
interests (POIs) in multiple languages. This is even superior to find local venues such as …
interests (POIs) in multiple languages. This is even superior to find local venues such as …
Dual-grained human mobility learning for location-aware trip recommendation with spatial–temporal graph knowledge fusion
Trip recommendation is a popular and significant location-aware service that can help
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
Forecasting traffic flow with spatial–temporal convolutional graph attention networks
X Zhang, Y Xu, Y Shao - Neural Computing and Applications, 2022 - Springer
Traffic flow prediction is crucial for intelligent transportation system, such as traffic
management, congestion alleviation and public risk assessment. Recently, attention …
management, congestion alleviation and public risk assessment. Recently, attention …
Graph Neural Network for spatiotemporal data: methods and applications
In the era of big data, there has been a surge in the availability of data containing rich spatial
and temporal information, offering valuable insights into dynamic systems and processes for …
and temporal information, offering valuable insights into dynamic systems and processes for …
A contextual master-slave framework on urban region graph for urban village detection
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the
rapid urbanization in a city. Since there are high levels of social inequality and social risks in …
rapid urbanization in a city. Since there are high levels of social inequality and social risks in …
Mgeo: Multi-modal geographic language model pre-training
Query and point of interest (POI) matching is a core task in location-based services~(LBS),
eg, navigation maps. It connects users' intent with real-world geographic information. Lately …
eg, navigation maps. It connects users' intent with real-world geographic information. Lately …