Xiangjie Kong
Biographic Data
| ID | 9225641 |
|---|---|
| NAME | Xiangjie Kong |
| GIVEN NAMES | Xiangjie |
| FAMILY NAME | Kong |
| SIGNATURE | KONG X |
| AFFILIATIONS | Zhejiang University of Technology |
| ORCID | 0000-0003-2698-3319 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Urban Overtourism Detection Based on Graph Temporal Convolutional Networks
Urban overtourism results in heavy traffic, degraded tourist experiences, and overloaded infrastructure. Detecting urban overtourism at the early stage is important to minimize the adverse effects. However, urban overtourism detection (UOD) is a challenging task due to ambiguity, sparsity, and complex spatiotemporal relations of overtourism. In this article, we propose a novel UOD framework based on graph temporal convolutional networks (TCNs) to…
KGNext
The next point-of-interest (POI) recommendation aims to predict users’ future movements based on their historical trajectories. However, in reality, users may provide uncertain check-in records, resulting in uploaded data that lack precise location information and is instead ambiguous. Despite this challenge, only a limited number of studies have addressed this issue, often overlooking the intricate interactions among users, POIs, and POI categor…
FedVCP
Intelligent vehicle applications, such as autonomous driving and collision avoidance, put forward a higher demand for precise positioning of vehicles. The current widely used global navigation satellite systems (GNSS) cannot meet the precision requirements of the submeter level. Due to the development of sensing techniques and vehicle-to-infrastructure (V2I) communications, some vehicles can interact with surrounding landmarks to achieve precise …
No prominent works on this page.
FedVCP
Intelligent vehicle applications, such as autonomous driving and collision avoidance, put forward a higher demand for precise positioning of vehicles. The current widely used global navigation satellite systems (GNSS) cannot meet the precision requirements of the submeter level. Due to the development of sensing techniques and vehicle-to-infrastructure (V2I) communications, some vehicles can interact with surrounding landmarks to achieve precise …
Urban Overtourism Detection Based on Graph Temporal Convolutional Networks
Urban overtourism results in heavy traffic, degraded tourist experiences, and overloaded infrastructure. Detecting urban overtourism at the early stage is important to minimize the adverse effects. However, urban overtourism detection (UOD) is a challenging task due to ambiguity, sparsity, and complex spatiotemporal relations of overtourism. In this article, we propose a novel UOD framework based on graph temporal convolutional networks (TCNs) to…
KGNext
The next point-of-interest (POI) recommendation aims to predict users’ future movements based on their historical trajectories. However, in reality, users may provide uncertain check-in records, resulting in uploaded data that lack precise location information and is instead ambiguous. Despite this challenge, only a limited number of studies have addressed this issue, often overlooking the intricate interactions among users, POIs, and POI categor…
Computer Science (3 works) · Engineering (2 works) · Graph (2 works) · Theoretical Computer Science (2 works) · Advanced Graph Neural Networks (1 work) · Artificial Intelligence (1 work) · Computer network (1 work) · Computer security (1 work) · Data exchange (1 work) · Data mining (1 work)