A5102676483- Traffic Prediction and Management Techniques
- Multi-Agent Systems and Negotiation
- Advanced Graph Neural Networks
- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- Human Mobility and Location-Based Analysis
- Transportation Planning and Optimization
- Geographic Information Systems Studies
- Text and Document Classification Technologies
Hong Kong University of Science and Technology
2024
University of Hong Kong
2024
Learning effective geospatial embeddings is crucial for a series of applications such as city analytics and earth monitoring. However, learning comprehensive region representations presents two significant challenges: first, the deficiency intra-region feature representation; second, difficulty from intricate inter-region dependencies. In this paper, we present GeoHG, an heterogeneous graph structure various downstream tasks. Specifically, tailor satellite image representation through...
Real-world data is represented in both structured (e.g., graph connections) and unstructured textual, visual information) formats, encompassing complex relationships that include explicit links (such as social connections user behaviors) implicit interdependencies among semantic entities, often illustrated through knowledge graphs. In this work, we propose GraphAgent, an automated agent pipeline addresses dependencies graph-enhanced inter-dependencies, aligning with practical scenarios for...
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (e.g., geographical, traffic, social media, and environmental data) modalities spatio-temporal, visual, textual modalities). Recently, we are witnessing rising trend that utilizes various deep-learning methods facilitate in smart cities. To this end, propose first survey systematically reviews latest advancements...