Amirhossein Vahdat
Biographic Data
| ID | 9965149 |
|---|---|
| NAME | Amirhossein Vahdat |
| GIVEN NAMES | Amirhossein |
| FAMILY NAME | Vahdat |
| SIGNATURE | VAHDAT A |
| AFFILIATIONS | Centre de Géomatique du Québec |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
A Semantic Collaborative Filtering-Based Recommendation System to Enhance Geospatial Data Discovery in Geoportals
Traditional geoportals depend primarily on keyword-based search, which often fails to retrieve relevant datasets when metadata are heterogeneous, incomplete, or inconsistent with user terminology. This limitation reduces the efficiency of data discovery and selection, particularly in domains where metadata quality varies widely. This study aims to address this challenge by developing a semantic collaborative filtering recommendation system design…
Development of an Ontology-Based Framework to Enhance Geospatial Data Discovery and Selection in Geoportals for Natural-Hazard Early Warning Systems
Discovering and selecting relevant geospatial datasets from heterogeneous sources remains difficult in conventional geoportals, where keyword-based search often fails to capture thematic relationships or user intent. This article presents an ontology-based framework that augments geoportals with semantic-aware discovery and selection. The contributions are as follows: (1) the geospatial metadata ontology (GMO), which reuses W3C and OGC ontologies…
No prominent works on this page.
A Semantic Collaborative Filtering-Based Recommendation System to Enhance Geospatial Data Discovery in Geoportals
Traditional geoportals depend primarily on keyword-based search, which often fails to retrieve relevant datasets when metadata are heterogeneous, incomplete, or inconsistent with user terminology. This limitation reduces the efficiency of data discovery and selection, particularly in domains where metadata quality varies widely. This study aims to address this challenge by developing a semantic collaborative filtering recommendation system design…
Development of an Ontology-Based Framework to Enhance Geospatial Data Discovery and Selection in Geoportals for Natural-Hazard Early Warning Systems
Discovering and selecting relevant geospatial datasets from heterogeneous sources remains difficult in conventional geoportals, where keyword-based search often fails to capture thematic relationships or user intent. This article presents an ontology-based framework that augments geoportals with semantic-aware discovery and selection. The contributions are as follows: (1) the geospatial metadata ontology (GMO), which reuses W3C and OGC ontologies…
Data Management and Algorithms (2 works) · Geographic Information Systems Studies (2 works) · Geospatial analysis (2 works) · Knowledge extraction (2 works) · Metadata (2 works) · Ontology (2 works) · Advanced Computational Techniques and Applications (1 works) · Association rule learning (1 works) · Cluster analysis (1 works) · Collaborative filtering (1 works)