Hang Feng
Datos Biográficos
| ID | 8318878 |
|---|---|
| NOMBRE | Hang Feng |
| NOMBRES | Hang |
| APELLIDO | Feng |
| FIRMA | FENG H |
| AFILIACIONES | Zhengzhou University |
| ORCID | 0000-0002-8771-9573 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2020 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 0 |
Extracting Geoscientific Dataset Names from the Literature Based on the Hierarchical Temporal Memory Model
Extracting geoscientific dataset names from the literature is crucial for building a literature–data association network, which can help readers access the data quickly through the Internet. However, the existing named-entity extraction methods have low accuracy in extracting geoscientific dataset names from unstructured text because geoscientific dataset names are a complex combination of multiple elements, such as geospatial coverage, temporal …
Exploring key factors of medical tourism and its relation with tourism attraction and re-visit intention
Tourism is a globalized industry. Health, wellness and medical tourism are recognized as one of the most developed and thriving in the tourism industry. The purpose of this study is to explore the key factors of medical tourism and discuss its relation with tourism attraction and re-visit intention. The results reveal that: (1) The key criteria are doctor’s expertise and reputation, health evaluation, international certified doctors and staffs, t…
Sin obras prominentes en esta página.
Exploring key factors of medical tourism and its relation with tourism attraction and re-visit intention
Tourism is a globalized industry. Health, wellness and medical tourism are recognized as one of the most developed and thriving in the tourism industry. The purpose of this study is to explore the key factors of medical tourism and discuss its relation with tourism attraction and re-visit intention. The results reveal that: (1) The key criteria are doctor’s expertise and reputation, health evaluation, international certified doctors and staffs, t…
Extracting Geoscientific Dataset Names from the Literature Based on the Hierarchical Temporal Memory Model
Extracting geoscientific dataset names from the literature is crucial for building a literature–data association network, which can help readers access the data quickly through the Internet. However, the existing named-entity extraction methods have low accuracy in extracting geoscientific dataset names from unstructured text because geoscientific dataset names are a complex combination of multiple elements, such as geospatial coverage, temporal …
Advanced Graph Neural Networks (1 obras) · Artificial Intelligence (1 obras) · Biomedical Text Mining and Ontologies (1 obras) · Business (1 obras) · Certification (1 obras) · Computer Science (1 obras) · Data mining (1 obras) · Diverse Aspects of Tourism Research (1 obras) · Global Healthcare and Medical Tourism (1 obras) · Health care (1 obras)