SRC
| Autor: | Tianyuan Huang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Structure (mathematical logic)
Computer science Movement (music) Node (networking) Network embedding 02 engineering and technology General Medicine Field survey Individual level Data science Urban planning 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Vector space representation |
| Zdroj: | SIGSPATIAL/GIS |
| ISSN: | 1946-7729 |
| DOI: | 10.1145/3383653.3383655 |
| Popis: | This study investigates human activity community in a city by conceptualizing it as a network embedding problem. In order to learn the latent representations of activity-travel patterns from individual daily trajectories, network embedding learns a vector space representation for each type of activity place as a node connected by movement links to preserve the structure of individual activities. The proposed approach is applied to mobile positioning data at the individual level obtained for a weekday from volunteers at Guangzhou City. Assessments are conducted to validate individual decision making for several types of activities by a field survey. This study contributes to a general framework for discovering individual activity-travel patterns from human movement trajectories. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|