Imad Afyouni
Biographic Data
| ID | 9967440 |
|---|---|
| NAME | Imad Afyouni |
| GIVEN NAMES | Imad |
| FAMILY NAME | Afyouni |
| SIGNATURE | AFYOUNI I |
| AFFILIATIONS | University of Sharjah |
| ORCID | 0000-0001-6686-3069 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Spatio-Temporal Sentiment Mining of Covid-19 Arabic Social Media
Since the recent outbreak of COVID-19, many scientists have started working on distinct challenges related to mining the available large datasets from social media as an effective asset to understand people’s responses to the pandemic. This study presents a comprehensive social data mining approach to provide in-depth insights related to the COVID-19 pandemic and applied to the Arabic language. We first developed a technique to infer geospatial i…
Representation
The objective of this entry is to review current spatial data models and mobile data management techniques available for indoor spaces. In particular, the role of contextual and semantic dimensions when representing moving objects and deriving navigation services in indoor spaces is studied. A series of recommendations are suggested for the development of data management approaches, querying techniques, and indoor location‐based services, and som…
No prominent works on this page.
Representation
The objective of this entry is to review current spatial data models and mobile data management techniques available for indoor spaces. In particular, the role of contextual and semantic dimensions when representing moving objects and deriving navigation services in indoor spaces is studied. A series of recommendations are suggested for the development of data management approaches, querying techniques, and indoor location‐based services, and som…
Spatio-Temporal Sentiment Mining of Covid-19 Arabic Social Media
Since the recent outbreak of COVID-19, many scientists have started working on distinct challenges related to mining the available large datasets from social media as an effective asset to understand people’s responses to the pandemic. This study presents a comprehensive social data mining approach to provide in-depth insights related to the COVID-19 pandemic and applied to the Arabic language. We first developed a technique to infer geospatial i…
Computer Science (2 works) · Data science (2 works) · Information retrieval (2 works) · Arabic (1 work) · Cartography (1 work) · Current (fluid) (1 work) · Data Management and Algorithms (1 work) · Data mining (1 work) · Data-Driven Disease Surveillance (1 work) · Generalization (1 work)